Geiser C. Challco geiser@alumni.usp.br
NOTE:
dv = "score.tde"
dv.pos = "score.tde.pos"
dv.pre = "score.tde.pre"
fatores2 <- c("Sexo","Zona","Cor.Raca","Serie","score.tde.quintile")
lfatores2 <- as.list(fatores2)
names(lfatores2) <- fatores2
fatores1 <- c("grupo", fatores2)
lfatores1 <- as.list(fatores1)
names(lfatores1) <- fatores1
lfatores <- c(lfatores1)
color <- list()
color[["prepost"]] = c("#ffee65","#f28e2B")
color[["grupo"]] = c("#bcbd22","#008000")
color[["Sexo"]] = c("#FF007F","#4D4DFF")
color[["Zona"]] = c("#AA00FF","#00CCCC")
color[["Cor.Raca"]] = c(
"Parda"="#b97100","Indígena"="#9F262F",
"Branca"="#87c498", "Preta"="#848283","Amarela"="#D6B91C"
)
level <- list()
level[["grupo"]] = c("Controle","Experimental")
level[["Sexo"]] = c("F","M")
level[["Zona"]] = c("Rural","Urbana")
level[["Cor.Raca"]] = c("Parda","Indígena","Branca", "Preta","Amarela")
level[["Serie"]] = c("6 ano","7 ano","8 ano","9 ano")
# ..
ymin <- 0
ymax <- 0
ymin.ci <- 0
ymax.ci <- 0
color[["grupo:Sexo"]] = c(
"Controle:F"="#ff99cb", "Controle:M"="#b7b7ff",
"Experimental:F"="#FF007F", "Experimental:M"="#4D4DFF",
"Controle.F"="#ff99cb", "Controle.M"="#b7b7ff",
"Experimental.F"="#FF007F", "Experimental.M"="#4D4DFF"
)
color[["grupo:Zona"]] = c(
"Controle:Rural"="#b2efef","Controle:Urbana"="#e5b2ff",
"Experimental:Rural"="#00CCCC", "Experimental:Urbana"="#AA00FF",
"Controle.Rural"="#b2efef","Controle.Urbana"="#e5b2ff",
"Experimental.Rural"="#00CCCC", "Experimental.Urbana"="#AA00FF"
)
color[["grupo:Cor.Raca"]] = c(
"Controle:Parda"="#e3c699", "Experimental:Parda"="#b97100",
"Controle:Indígena"="#e2bdc0", "Experimental:Indígena"="#9F262F",
"Controle:Branca"="#c0e8cb", "Experimental:Branca"="#87c498",
"Controle:Preta"="#dad9d9", "Experimental:Preta"="#848283",
"Controle:Amarela"="#eee3a4", "Experimental:Amarela"="#D6B91C",
"Controle.Parda"="#e3c699", "Experimental.Parda"="#b97100",
"Controle.Indígena"="#e2bdc0", "Experimental.Indígena"="#9F262F",
"Controle.Branca"="#c0e8cb", "Experimental.Branca"="#87c498",
"Controle.Preta"="#dad9d9", "Experimental.Preta"="#848283",
"Controle.Amarela"="#eee3a4", "Experimental.Amarela"="#D6B91C"
)
for (coln in c("vocab","vocab.teach","vocab.non.teach","score.tde",
"TFL.lidas.per.min","TFL.corretas.per.min","TFL.erradas.per.min","TFL.omitidas.per.min",
"leitura.compreensao")) {
color[[paste0(coln,".quintile")]] = c("#BF0040","#FF0000","#800080","#0000FF","#4000BF")
level[[paste0(coln,".quintile")]] = c("1st quintile","2nd quintile","3rd quintile","4th quintile","5th quintile")
color[[paste0("grupo:",coln,".quintile")]] = c(
"Experimental.1st quintile"="#BF0040", "Controle.1st quintile"="#d8668c",
"Experimental.2nd quintile"="#FF0000", "Controle.2nd quintile"="#ff7f7f",
"Experimental.3rd quintile"="#8fce00", "Controle.3rd quintile"="#ddf0b2",
"Experimental.4th quintile"="#0000FF", "Controle.4th quintile"="#b2b2ff",
"Experimental.5th quintile"="#4000BF", "Controle.5th quintile"="#b299e5",
"Experimental:1st quintile"="#BF0040", "Controle:1st quintile"="#d8668c",
"Experimental:2nd quintile"="#FF0000", "Controle:2nd quintile"="#ff7f7f",
"Experimental:3rd quintile"="#8fce00", "Controle:3rd quintile"="#ddf0b2",
"Experimental:4th quintile"="#0000FF", "Controle:4th quintile"="#b2b2ff",
"Experimental:5th quintile"="#4000BF", "Controle:5th quintile"="#b299e5")
}
tdat <- read_excel("../data/data.xlsx", sheet = "sumary")
tdat <- tdat[!is.na(tdat[["WG.Grupo"]]),]
tdat$grupo <- factor(tdat[["WG.Grupo"]], level[["grupo"]])
gdat <- tdat[which(is.na(tdat$Necessidade.Deficiencia) & !is.na(tdat$WG.Grupo)),]
dat <- gdat
dat$grupo <- factor(dat[["WG.Grupo"]], level[["grupo"]])
for (coln in c(names(lfatores))) {
dat[[coln]] <- factor(dat[[coln]], level[[coln]][level[[coln]] %in% unique(dat[[coln]])])
}
dat <- dat[which(!is.na(dat[[dv.pre]]) & !is.na(dat[[dv.pos]])),]
dat <- dat[,c("id",names(lfatores),dv.pre,dv.pos)]
dat.long <- rbind(dat, dat)
dat.long$time <- c(rep("pre", nrow(dat)), rep("pos", nrow(dat)))
dat.long$time <- factor(dat.long$time, c("pre","pos"))
dat.long[[dv]] <- c(dat[[dv.pre]], dat[[dv.pos]])
for (f in c("grupo", names(lfatores))) {
if (is.null(color[[f]]) && length(unique(dat[[f]])) > 0)
color[[f]] <- distinctColorPalette(length(unique(dat[[f]])))
}
for (f in c(fatores2)) {
if (is.null(color[[paste0("grupo:",f)]]) && length(unique(dat[[f]])) > 0)
color[[paste0("grupo:",f)]] <- distinctColorPalette(length(unique(dat[["grupo"]]))*length(unique(dat[[f]])))
}
ldat <- list()
laov <- list()
lpwc <- list()
lemms <- list()
df <- get.descriptives(dat, c(dv.pre, dv.pos), c("grupo"),
include.global = T, symmetry.test = T, normality.test = F)
df <- plyr::rbind.fill(
df, do.call(plyr::rbind.fill, lapply(lfatores2, FUN = function(f) {
if (nrow(dat) > 0 && sum(!is.na(unique(dat[[f]]))) > 1)
get.descriptives(dat, c(dv.pre,dv.pos), c("grupo", f),
symmetry.test = T, normality.test = F)
}))
)
## Warning: There was 1 warning in `mutate()`.
## ℹ In argument: `ci = abs(stats::qt(alpha/2, .data$n - 1) * .data$se)`.
## Caused by warning:
## ! There was 1 warning in `mutate()`.
## ℹ In argument: `ci = abs(stats::qt(alpha/2, .data$n - 1) * .data$se)`.
## Caused by warning in `stats::qt()`:
## ! NaNs produced
## There was 1 warning in `mutate()`.
## ℹ In argument: `ci = abs(stats::qt(alpha/2, .data$n - 1) * .data$se)`.
## Caused by warning:
## ! There was 1 warning in `mutate()`.
## ℹ In argument: `ci = abs(stats::qt(alpha/2, .data$n - 1) * .data$se)`.
## Caused by warning in `stats::qt()`:
## ! NaNs produced
df <- df[,c(fatores1[fatores1 %in% colnames(df)],"variable",
colnames(df)[!colnames(df) %in% c(fatores1,"variable")])]
| grupo | Sexo | Zona | Cor.Raca | Serie | score.tde.quintile | variable | n | mean | median | min | max | sd | se | ci | iqr | symmetry | skewness | kurtosis |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Controle | score.tde.pre | 485 | 37.631 | 44.0 | 0 | 75 | 19.176 | 0.871 | 1.711 | 33.00 | YES | -0.443 | -1.017 | |||||
| Experimental | score.tde.pre | 636 | 36.748 | 39.0 | 0 | 73 | 16.891 | 0.670 | 1.315 | 24.00 | YES | -0.303 | -0.711 | |||||
| score.tde.pre | 1121 | 37.130 | 41.0 | 0 | 75 | 17.912 | 0.535 | 1.050 | 28.00 | YES | -0.370 | -0.857 | ||||||
| Controle | score.tde.pos | 485 | 33.816 | 36.0 | 0 | 73 | 20.988 | 0.953 | 1.873 | 37.00 | YES | -0.108 | -1.287 | |||||
| Experimental | score.tde.pos | 636 | 35.376 | 38.0 | 0 | 74 | 18.900 | 0.749 | 1.472 | 30.00 | YES | -0.158 | -1.024 | |||||
| score.tde.pos | 1121 | 34.701 | 37.0 | 0 | 74 | 19.836 | 0.592 | 1.162 | 33.00 | YES | -0.145 | -1.138 | ||||||
| Controle | F | score.tde.pre | 247 | 40.652 | 46.0 | 0 | 72 | 17.259 | 1.098 | 2.163 | 24.50 | NO | -0.692 | -0.519 | ||||
| Controle | M | score.tde.pre | 238 | 34.496 | 42.0 | 0 | 75 | 20.552 | 1.332 | 2.624 | 37.00 | YES | -0.173 | -1.308 | ||||
| Experimental | F | score.tde.pre | 319 | 39.408 | 43.0 | 0 | 73 | 16.802 | 0.941 | 1.851 | 25.00 | YES | -0.460 | -0.599 | ||||
| Experimental | M | score.tde.pre | 317 | 34.073 | 36.0 | 0 | 71 | 16.580 | 0.931 | 1.832 | 23.00 | YES | -0.175 | -0.723 | ||||
| Controle | F | score.tde.pos | 247 | 36.567 | 42.0 | 0 | 72 | 19.883 | 1.265 | 2.492 | 35.00 | YES | -0.290 | -1.208 | ||||
| Controle | M | score.tde.pos | 238 | 30.962 | 28.5 | 0 | 73 | 21.752 | 1.410 | 2.778 | 37.00 | YES | 0.098 | -1.291 | ||||
| Experimental | F | score.tde.pos | 319 | 38.138 | 42.0 | 0 | 73 | 19.397 | 1.086 | 2.137 | 32.00 | YES | -0.311 | -1.059 | ||||
| Experimental | M | score.tde.pos | 317 | 32.596 | 34.0 | 0 | 74 | 17.992 | 1.011 | 1.988 | 29.00 | YES | -0.050 | -0.909 | ||||
| Controle | Rural | score.tde.pre | 243 | 36.181 | 43.0 | 0 | 69 | 19.626 | 1.259 | 2.480 | 34.50 | YES | -0.429 | -1.220 | ||||
| Controle | Urbana | score.tde.pre | 109 | 39.468 | 43.0 | 1 | 75 | 18.034 | 1.727 | 3.424 | 26.00 | YES | -0.361 | -0.676 | ||||
| Controle | score.tde.pre | 133 | 38.774 | 45.0 | 0 | 73 | 19.183 | 1.663 | 3.290 | 32.00 | YES | -0.480 | -1.003 | |||||
| Experimental | Rural | score.tde.pre | 284 | 34.592 | 35.5 | 0 | 73 | 17.467 | 1.036 | 2.040 | 25.25 | YES | -0.140 | -0.823 | ||||
| Experimental | Urbana | score.tde.pre | 167 | 37.850 | 42.0 | 0 | 71 | 16.633 | 1.287 | 2.541 | 22.00 | YES | -0.491 | -0.519 | ||||
| Experimental | score.tde.pre | 185 | 39.065 | 42.0 | 0 | 69 | 15.877 | 1.167 | 2.303 | 23.00 | YES | -0.345 | -0.691 | |||||
| Controle | Rural | score.tde.pos | 243 | 34.243 | 39.0 | 0 | 72 | 21.515 | 1.380 | 2.719 | 38.00 | YES | -0.201 | -1.321 | ||||
| Controle | Urbana | score.tde.pos | 109 | 29.835 | 26.0 | 0 | 73 | 20.374 | 1.951 | 3.868 | 37.00 | YES | 0.237 | -1.198 | ||||
| Controle | score.tde.pos | 133 | 36.301 | 39.0 | 0 | 73 | 20.179 | 1.750 | 3.461 | 34.00 | YES | -0.200 | -1.185 | |||||
| Experimental | Rural | score.tde.pos | 284 | 33.627 | 33.0 | 0 | 72 | 19.232 | 1.141 | 2.246 | 33.00 | YES | 0.039 | -1.088 | ||||
| Experimental | Urbana | score.tde.pos | 167 | 34.108 | 38.0 | 0 | 74 | 18.899 | 1.462 | 2.887 | 30.50 | YES | -0.228 | -1.049 | ||||
| Experimental | score.tde.pos | 185 | 39.205 | 42.0 | 0 | 73 | 17.909 | 1.317 | 2.598 | 26.00 | YES | -0.387 | -0.775 | |||||
| Controle | Parda | score.tde.pre | 162 | 36.741 | 43.0 | 0 | 66 | 18.900 | 1.485 | 2.932 | 31.25 | NO | -0.595 | -0.975 | ||||
| Controle | Indígena | score.tde.pre | 11 | 42.000 | 46.0 | 4 | 65 | 17.297 | 5.215 | 11.621 | 9.50 | NO | -1.005 | -0.104 | ||||
| Controle | Branca | score.tde.pre | 50 | 41.460 | 46.0 | 2 | 67 | 16.942 | 2.396 | 4.815 | 14.50 | NO | -0.821 | -0.311 | ||||
| Controle | score.tde.pre | 262 | 37.267 | 43.0 | 0 | 75 | 19.798 | 1.223 | 2.408 | 34.00 | YES | -0.268 | -1.181 | |||||
| Experimental | Parda | score.tde.pre | 190 | 34.253 | 35.0 | 0 | 68 | 17.537 | 1.272 | 2.510 | 27.00 | YES | -0.133 | -0.931 | ||||
| Experimental | Indígena | score.tde.pre | 15 | 27.067 | 26.0 | 6 | 54 | 17.065 | 4.406 | 9.450 | 27.00 | YES | 0.126 | -1.422 | ||||
| Experimental | Branca | score.tde.pre | 61 | 34.623 | 36.0 | 0 | 73 | 19.728 | 2.526 | 5.053 | 33.00 | YES | -0.045 | -1.037 | ||||
| Experimental | Amarela | score.tde.pre | 1 | 23.000 | 23.0 | 23 | 23 | 0.00 | few data | 0.000 | 0.000 | |||||||
| Experimental | score.tde.pre | 369 | 38.816 | 42.0 | 0 | 71 | 15.723 | 0.819 | 1.610 | 21.00 | YES | -0.438 | -0.449 | |||||
| Controle | Parda | score.tde.pos | 162 | 32.463 | 35.0 | 0 | 68 | 20.798 | 1.634 | 3.227 | 39.75 | YES | -0.166 | -1.437 | ||||
| Controle | Indígena | score.tde.pos | 11 | 45.636 | 52.0 | 4 | 63 | 19.931 | 6.009 | 13.390 | 19.50 | NO | -0.968 | -0.645 | ||||
| Controle | Branca | score.tde.pos | 50 | 34.300 | 38.0 | 0 | 72 | 20.518 | 2.902 | 5.831 | 34.75 | YES | -0.208 | -1.184 | ||||
| Controle | score.tde.pos | 262 | 34.065 | 34.0 | 0 | 73 | 21.180 | 1.309 | 2.577 | 36.00 | YES | -0.024 | -1.252 | |||||
| Experimental | Parda | score.tde.pos | 190 | 32.447 | 30.0 | 0 | 71 | 19.467 | 1.412 | 2.786 | 32.75 | YES | 0.082 | -1.112 | ||||
| Experimental | Indígena | score.tde.pos | 15 | 30.333 | 26.0 | 1 | 57 | 17.715 | 4.574 | 9.810 | 30.50 | YES | 0.117 | -1.542 | ||||
| Experimental | Branca | score.tde.pos | 61 | 33.311 | 34.0 | 0 | 72 | 21.189 | 2.713 | 5.427 | 34.00 | YES | 0.076 | -1.201 | ||||
| Experimental | Amarela | score.tde.pos | 1 | 23.000 | 23.0 | 23 | 23 | 0.00 | few data | 0.000 | 0.000 | |||||||
| Experimental | score.tde.pos | 369 | 37.463 | 40.0 | 0 | 74 | 18.045 | 0.939 | 1.847 | 27.00 | YES | -0.336 | -0.844 | |||||
| Controle | 6 ano | score.tde.pre | 134 | 28.993 | 26.5 | 0 | 63 | 19.526 | 1.687 | 3.336 | 36.00 | YES | 0.057 | -1.526 | ||||
| Controle | 7 ano | score.tde.pre | 141 | 34.716 | 41.0 | 0 | 69 | 17.842 | 1.503 | 2.971 | 29.00 | YES | -0.265 | -1.162 | ||||
| Controle | 8 ano | score.tde.pre | 89 | 42.584 | 46.0 | 0 | 72 | 16.382 | 1.737 | 3.451 | 17.00 | NO | -0.833 | 0.214 | ||||
| Controle | 9 ano | score.tde.pre | 121 | 46.950 | 51.0 | 0 | 75 | 17.124 | 1.557 | 3.082 | 15.00 | NO | -1.124 | 0.589 | ||||
| Experimental | 6 ano | score.tde.pre | 159 | 29.000 | 29.0 | 0 | 65 | 15.950 | 1.265 | 2.498 | 24.50 | YES | -0.043 | -0.909 | ||||
| Experimental | 7 ano | score.tde.pre | 187 | 36.540 | 38.0 | 0 | 68 | 14.891 | 1.089 | 2.148 | 21.50 | YES | -0.195 | -0.682 | ||||
| Experimental | 8 ano | score.tde.pre | 143 | 39.000 | 44.0 | 0 | 73 | 18.129 | 1.516 | 2.997 | 25.50 | NO | -0.515 | -0.734 | ||||
| Experimental | 9 ano | score.tde.pre | 147 | 43.204 | 45.0 | 0 | 71 | 15.845 | 1.307 | 2.583 | 22.00 | NO | -0.641 | -0.044 | ||||
| Controle | 6 ano | score.tde.pos | 134 | 24.231 | 19.5 | 0 | 66 | 20.155 | 1.741 | 3.444 | 40.00 | YES | 0.381 | -1.295 | ||||
| Controle | 7 ano | score.tde.pos | 141 | 28.362 | 22.0 | 0 | 72 | 20.646 | 1.739 | 3.437 | 37.00 | YES | 0.379 | -1.190 | ||||
| Controle | 8 ano | score.tde.pos | 89 | 39.787 | 43.0 | 0 | 71 | 17.900 | 1.897 | 3.771 | 28.00 | NO | -0.521 | -0.552 | ||||
| Controle | 9 ano | score.tde.pos | 121 | 46.397 | 50.0 | 0 | 73 | 16.448 | 1.495 | 2.960 | 20.00 | NO | -0.786 | 0.049 | ||||
| Experimental | 6 ano | score.tde.pos | 159 | 24.094 | 22.0 | 0 | 65 | 16.759 | 1.329 | 2.625 | 26.00 | NO | 0.518 | -0.626 | ||||
| Experimental | 7 ano | score.tde.pos | 187 | 33.524 | 36.0 | 0 | 69 | 17.147 | 1.254 | 2.474 | 27.50 | YES | -0.063 | -0.934 | ||||
| Experimental | 8 ano | score.tde.pos | 143 | 41.042 | 45.0 | 0 | 73 | 19.177 | 1.604 | 3.170 | 26.50 | NO | -0.568 | -0.652 | ||||
| Experimental | 9 ano | score.tde.pos | 147 | 44.422 | 48.0 | 0 | 74 | 16.143 | 1.331 | 2.631 | 22.50 | NO | -0.733 | 0.081 | ||||
| Controle | 1st quintile | score.tde.pre | 113 | 9.230 | 10.0 | 0 | 18 | 5.560 | 0.523 | 1.036 | 9.00 | YES | -0.093 | -1.227 | ||||
| Controle | 2nd quintile | score.tde.pre | 59 | 24.542 | 25.0 | 19 | 31 | 3.780 | 0.492 | 0.985 | 6.00 | YES | -0.056 | -1.175 | ||||
| Controle | 3rd quintile | score.tde.pre | 54 | 38.815 | 39.5 | 32 | 42 | 3.004 | 0.409 | 0.820 | 5.00 | NO | -0.510 | -1.049 | ||||
| Controle | 4th quintile | score.tde.pre | 135 | 47.370 | 47.0 | 43 | 51 | 2.579 | 0.222 | 0.439 | 4.50 | YES | -0.238 | -1.107 | ||||
| Controle | 5th quintile | score.tde.pre | 124 | 58.621 | 58.0 | 52 | 75 | 5.367 | 0.482 | 0.954 | 8.00 | NO | 0.794 | 0.036 | ||||
| Experimental | 1st quintile | score.tde.pre | 112 | 9.777 | 10.0 | 0 | 18 | 5.445 | 0.515 | 1.020 | 9.25 | YES | -0.202 | -1.150 | ||||
| Experimental | 2nd quintile | score.tde.pre | 117 | 25.855 | 26.0 | 19 | 31 | 3.422 | 0.316 | 0.627 | 6.00 | YES | -0.218 | -1.044 | ||||
| Experimental | 3rd quintile | score.tde.pre | 141 | 37.383 | 38.0 | 32 | 42 | 3.177 | 0.268 | 0.529 | 6.00 | YES | -0.147 | -1.221 | ||||
| Experimental | 4th quintile | score.tde.pre | 132 | 46.697 | 47.0 | 43 | 51 | 2.489 | 0.217 | 0.429 | 4.25 | YES | 0.144 | -1.180 | ||||
| Experimental | 5th quintile | score.tde.pre | 134 | 58.336 | 57.5 | 52 | 73 | 5.029 | 0.434 | 0.859 | 8.00 | NO | 0.688 | -0.352 | ||||
| Controle | 1st quintile | score.tde.pos | 113 | 8.522 | 5.0 | 0 | 44 | 8.588 | 0.808 | 1.601 | 12.00 | NO | 1.083 | 1.171 | ||||
| Controle | 2nd quintile | score.tde.pos | 59 | 19.966 | 20.0 | 0 | 66 | 12.947 | 1.686 | 3.374 | 13.50 | NO | 1.282 | 2.560 | ||||
| Controle | 3rd quintile | score.tde.pos | 54 | 30.185 | 28.5 | 2 | 62 | 15.298 | 2.082 | 4.176 | 22.25 | YES | 0.232 | -0.869 | ||||
| Controle | 4th quintile | score.tde.pos | 135 | 43.215 | 46.0 | 14 | 63 | 11.360 | 0.978 | 1.934 | 16.00 | NO | -0.680 | -0.300 | ||||
| Controle | 5th quintile | score.tde.pos | 124 | 54.806 | 56.0 | 22 | 73 | 10.905 | 0.979 | 1.938 | 11.25 | NO | -0.916 | 0.870 | ||||
| Experimental | 1st quintile | score.tde.pos | 112 | 11.384 | 10.0 | 0 | 51 | 9.500 | 0.898 | 1.779 | 12.00 | NO | 1.241 | 2.205 | ||||
| Experimental | 2nd quintile | score.tde.pos | 117 | 24.675 | 25.0 | 0 | 60 | 12.203 | 1.128 | 2.234 | 16.00 | YES | 0.028 | -0.429 | ||||
| Experimental | 3rd quintile | score.tde.pos | 141 | 34.872 | 37.0 | 0 | 64 | 13.013 | 1.096 | 2.167 | 18.00 | YES | -0.298 | -0.483 | ||||
| Experimental | 4th quintile | score.tde.pos | 132 | 45.030 | 47.0 | 10 | 69 | 10.621 | 0.924 | 1.829 | 11.00 | NO | -0.801 | 0.896 | ||||
| Experimental | 5th quintile | score.tde.pos | 134 | 55.791 | 57.0 | 14 | 74 | 10.619 | 0.917 | 1.814 | 12.00 | NO | -1.174 | 2.100 |
pdat = remove_group_data(dat[!is.na(dat[["grupo"]]),], "score.tde.pos", "grupo")
pdat.long <- rbind(pdat[,c("id","grupo")], pdat[,c("id","grupo")])
pdat.long[["time"]] <- c(rep("pre", nrow(pdat)), rep("pos", nrow(pdat)))
pdat.long[["time"]] <- factor(pdat.long[["time"]], c("pre","pos"))
pdat.long[["score.tde"]] <- c(pdat[["score.tde.pre"]], pdat[["score.tde.pos"]])
aov = anova_test(pdat, score.tde.pos ~ score.tde.pre + grupo)
laov[["grupo"]] <- get_anova_table(aov)
pwc <- emmeans_test(pdat, score.tde.pos ~ grupo, covariate = score.tde.pre,
p.adjust.method = "bonferroni")
pwc.long <- emmeans_test(dplyr::group_by_at(pdat.long, "grupo"),
score.tde ~ time,
p.adjust.method = "bonferroni")
lpwc[["grupo"]] <- plyr::rbind.fill(pwc, pwc.long)
ds <- get.descriptives(pdat, "score.tde.pos", "grupo", covar = "score.tde.pre")
ds <- merge(ds[ds$variable != "score.tde.pre",],
ds[ds$variable == "score.tde.pre", !colnames(ds) %in% c("variable")],
by = "grupo", all.x = T, suffixes = c("", ".score.tde.pre"))
ds <- merge(get_emmeans(pwc), ds, by = "grupo", suffixes = c(".emms", ""))
ds <- ds[,c("grupo","n","mean.score.tde.pre","se.score.tde.pre","mean","se",
"emmean","se.emms","conf.low","conf.high")]
colnames(ds) <- c("grupo", "N", paste0(c("M","SE")," (pre)"),
paste0(c("M","SE"), " (unadj)"),
paste0(c("M", "SE"), " (adj)"), "conf.low", "conf.high")
lemms[["grupo"]] <- ds
wdat = pdat
res = residuals(lm(score.tde.pos ~ score.tde.pre + grupo, data = wdat))
non.normal = getNonNormal(res, wdat$id, plimit = 0.05)
wdat = wdat[!wdat$id %in% non.normal,]
wdat.long <- rbind(wdat[,c("id","grupo")], wdat[,c("id","grupo")])
wdat.long[["time"]] <- c(rep("pre", nrow(wdat)), rep("pos", nrow(wdat)))
wdat.long[["time"]] <- factor(wdat.long[["time"]], c("pre","pos"))
wdat.long[["score.tde"]] <- c(wdat[["score.tde.pre"]], wdat[["score.tde.pos"]])
ldat[["grupo"]] = wdat
(non.normal)
## [1] "P962" "P1128" "P984" "P1129" "P3637" "P1126" "P1971" "P572" "P3021"
## [10] "P2871" "P1139" "P921" "P2858" "P3054" "P3019" "P2995" "P2848" "P2870"
## [19] "P1117" "P2929" "P929" "P2835" "P2983" "P2946" "P2865" "P2910" "P3007"
## [28] "P3015" "P2964" "P2975" "P2876" "P2937" "P2831" "P2953" "P2986" "P1018"
## [37] "P2950" "P2883" "P1878" "P2917" "P2866" "P2997" "P2880" "P908" "P2978"
## [46] "P2864" "P3005" "P2974" "P3026" "P2904" "P2994" "P1111" "P2846" "P2913"
## [55] "P2886" "P2905" "P3533" "P914" "P2888" "P2867" "P1983" "P3574" "P1840"
## [64] "P3545" "P2993" "P976" "P2973" "P2967" "P3029" "P3548" "P3000" "P2959"
## [73] "P2956" "P2982" "P3475" "P2854" "P1068" "P3476" "P3674" "P3660" "P2004"
## [82] "P3666" "P2190" "P2839" "P2861" "P1885" "P2947" "P606" "P1149" "P609"
## [91] "P2843" "P3228" "P2845" "P2868" "P2860" "P3024" "P2852" "P2990" "P2969"
## [100] "P809" "P2909" "P924" "P1914" "P1056" "P2847" "P1046" "P1118" "P541"
## [109] "P3651" "P3221" "P2903" "P2979" "P3537" "P2981" "P3237" "P1127" "P1916"
## [118] "P2832" "P1828" "P3571" "P996" "P2869" "P2836" "P2879" "P1900" "P2891"
## [127] "P3608" "P2882" "P2951" "P1673" "P993" "P1910" "P548" "P492" "P1887"
## [136] "P848" "P1964" "P859" "P2971" "P2922"
aov = anova_test(wdat, score.tde.pos ~ score.tde.pre + grupo)
laov[["grupo"]] <- merge(get_anova_table(aov), laov[["grupo"]],
by="Effect", suffixes = c("","'"))
(df = get_anova_table(aov))
## ANOVA Table (type II tests)
##
## Effect DFn DFd F p p<.05 ges
## 1 score.tde.pre 1 978 5874.442 0.00e+00 * 0.857
## 2 grupo 1 978 24.670 8.03e-07 * 0.025
| Effect | DFn | DFd | F | p | p<.05 | ges |
|---|---|---|---|---|---|---|
| score.tde.pre | 1 | 978 | 5874.442 | 0 | * | 0.857 |
| grupo | 1 | 978 | 24.670 | 0 | * | 0.025 |
pwc <- emmeans_test(wdat, score.tde.pos ~ grupo, covariate = score.tde.pre,
p.adjust.method = "bonferroni")
| term | .y. | group1 | group2 | df | statistic | p | p.adj | p.adj.signif |
|---|---|---|---|---|---|---|---|---|
| score.tde.pre*grupo | score.tde.pos | Controle | Experimental | 978 | -4.967 | 0 | 0 | **** |
pwc.long <- emmeans_test(dplyr::group_by_at(wdat.long, "grupo"),
score.tde ~ time,
p.adjust.method = "bonferroni")
lpwc[["grupo"]] <- merge(plyr::rbind.fill(pwc, pwc.long), lpwc[["grupo"]],
by=c("grupo","term",".y.","group1","group2"),
suffixes = c("","'"))
| grupo | term | .y. | group1 | group2 | df | statistic | p | p.adj | p.adj.signif |
|---|---|---|---|---|---|---|---|---|---|
| Controle | time | score.tde | pre | pos | 1958 | 1.465 | 0.143 | 0.143 | ns |
| Experimental | time | score.tde | pre | pos | 1958 | -0.402 | 0.688 | 0.688 | ns |
ds <- get.descriptives(wdat, "score.tde.pos", "grupo", covar = "score.tde.pre")
ds <- merge(ds[ds$variable != "score.tde.pre",],
ds[ds$variable == "score.tde.pre", !colnames(ds) %in% c("variable")],
by = "grupo", all.x = T, suffixes = c("", ".score.tde.pre"))
ds <- merge(get_emmeans(pwc), ds, by = "grupo", suffixes = c(".emms", ""))
ds <- ds[,c("grupo","n","mean.score.tde.pre","se.score.tde.pre","mean","se",
"emmean","se.emms","conf.low","conf.high")]
colnames(ds) <- c("grupo", "N", paste0(c("M","SE")," (pre)"),
paste0(c("M","SE"), " (unadj)"),
paste0(c("M", "SE"), " (adj)"), "conf.low", "conf.high")
lemms[["grupo"]] <- merge(ds, lemms[["grupo"]], by=c("grupo"), suffixes = c("","'"))
| grupo | N | M (pre) | SE (pre) | M (unadj) | SE (unadj) | M (adj) | SE (adj) | conf.low | conf.high |
|---|---|---|---|---|---|---|---|---|---|
| Controle | 424 | 37.351 | 0.975 | 35.432 | 1.018 | 35.112 | 0.358 | 34.409 | 35.815 |
| Experimental | 557 | 36.770 | 0.741 | 37.230 | 0.777 | 37.473 | 0.313 | 36.860 | 38.087 |
plots <- oneWayAncovaPlots(
wdat, "score.tde.pos", "grupo", aov, list("grupo"=pwc), addParam = c("mean_ci"),
font.label.size=10, step.increase=0.05, p.label="p.adj",
subtitle = which(aov$Effect == "grupo"))
if (!is.null(nrow(plots[["grupo"]]$data)))
plots[["grupo"]] +
ggplot2::ylab("Writing (TDE)") +
theme(axis.title = element_text(size = 14),
legend.text = element_text(size = 16),
plot.subtitle = element_text(size = 18)) +
if (ymin.ci < ymax.ci) ggplot2::ylim(ymin.ci, ymax.ci)
plots <- oneWayAncovaBoxPlots(
wdat, "score.tde.pos", "grupo", aov, pwc, covar = "score.tde.pre",
theme = "classic", color = color[["grupo"]],
subtitle = which(aov$Effect == "grupo"))
if (length(unique(wdat[["grupo"]])) > 1)
plots[["grupo"]] + ggplot2::ylab("Writing (TDE)") +
ggplot2::scale_x_discrete(labels=c('pre', 'pos')) +
if (ymin < ymax) ggplot2::ylim(ymin, ymax)
if (length(unique(wdat.long[["grupo"]])) > 1)
plots <- oneWayAncovaBoxPlots(
wdat.long, "score.tde", "grupo", aov, pwc.long,
pre.post = "time", theme = "classic", color = color$prepost)
if (length(unique(wdat.long[["grupo"]])) > 1)
plots[["grupo"]] + ggplot2::ylab("Writing (TDE)") +
if (ymin < ymax) ggplot2::ylim(ymin, ymax)
ggscatter(wdat, x = "score.tde.pre", y = "score.tde.pos", size = 0.5,
color = "grupo", add = "reg.line")+
stat_regline_equation(
aes(label = paste(..eq.label.., ..rr.label.., sep = "~~~~"), color = grupo)
) +
ggplot2::labs(subtitle = rstatix::get_test_label(aov, detailed = T, row = which(aov$Effect == "grupo"))) +
ggplot2::scale_color_manual(values = color[["grupo"]]) +
ggplot2::xlab("Writing (TDE)") +
ggplot2::ylab("Writing (TDE)") +
theme(axis.title = element_text(size = 14),
legend.text = element_text(size = 16),
plot.subtitle = element_text(size = 18)) +
if (ymin < ymax) ggplot2::ylim(ymin, ymax)
## Warning: The dot-dot notation (`..eq.label..`) was deprecated in ggplot2 3.4.0.
## ℹ Please use `after_stat(eq.label)` instead.
## ℹ The deprecated feature was likely used in the ggpubr package.
## Please report the issue at <https://github.com/kassambara/ggpubr/issues>.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
res <- augment(lm(score.tde.pos ~ score.tde.pre + grupo, data = wdat))
shapiro_test(res$.resid)
## # A tibble: 1 × 3
## variable statistic p.value
## <chr> <dbl> <dbl>
## 1 res$.resid 0.996 0.0185
levene_test(res, .resid ~ grupo)
## # A tibble: 1 × 4
## df1 df2 statistic p
## <int> <int> <dbl> <dbl>
## 1 1 979 0.00118 0.973
pdat = remove_group_data(dat[!is.na(dat[["grupo"]]) & !is.na(dat[["Sexo"]]),],
"score.tde.pos", c("grupo","Sexo"))
pdat = pdat[pdat[["Sexo"]] %in% do.call(
intersect, lapply(unique(pdat[["grupo"]]), FUN = function(x) {
unique(pdat[["Sexo"]][which(pdat[["grupo"]] == x)])
})),]
pdat[["grupo"]] = factor(pdat[["grupo"]], level[["grupo"]])
pdat[["Sexo"]] = factor(
pdat[["Sexo"]],
level[["Sexo"]][level[["Sexo"]] %in% unique(pdat[["Sexo"]])])
pdat.long <- rbind(pdat[,c("id","grupo","Sexo")], pdat[,c("id","grupo","Sexo")])
pdat.long[["time"]] <- c(rep("pre", nrow(pdat)), rep("pos", nrow(pdat)))
pdat.long[["time"]] <- factor(pdat.long[["time"]], c("pre","pos"))
pdat.long[["score.tde"]] <- c(pdat[["score.tde.pre"]], pdat[["score.tde.pos"]])
if (length(unique(pdat[["Sexo"]])) >= 2) {
aov = anova_test(pdat, score.tde.pos ~ score.tde.pre + grupo*Sexo)
laov[["grupo:Sexo"]] <- get_anova_table(aov)
}
if (length(unique(pdat[["Sexo"]])) >= 2) {
pwcs <- list()
pwcs[["Sexo"]] <- emmeans_test(
group_by(pdat, grupo), score.tde.pos ~ Sexo,
covariate = score.tde.pre, p.adjust.method = "bonferroni")
pwcs[["grupo"]] <- emmeans_test(
group_by(pdat, Sexo), score.tde.pos ~ grupo,
covariate = score.tde.pre, p.adjust.method = "bonferroni")
pwc <- plyr::rbind.fill(pwcs[["grupo"]], pwcs[["Sexo"]])
pwc <- pwc[,c("grupo","Sexo", colnames(pwc)[!colnames(pwc) %in% c("grupo","Sexo")])]
}
if (length(unique(pdat[["Sexo"]])) >= 2) {
pwc.long <- emmeans_test(dplyr::group_by_at(pdat.long, c("grupo","Sexo")),
score.tde ~ time,
p.adjust.method = "bonferroni")
lpwc[["grupo:Sexo"]] <- plyr::rbind.fill(pwc, pwc.long)
}
if (length(unique(pdat[["Sexo"]])) >= 2) {
ds <- get.descriptives(pdat, "score.tde.pos", c("grupo","Sexo"), covar = "score.tde.pre")
ds <- merge(ds[ds$variable != "score.tde.pre",],
ds[ds$variable == "score.tde.pre", !colnames(ds) %in% c("variable")],
by = c("grupo","Sexo"), all.x = T, suffixes = c("", ".score.tde.pre"))
ds <- merge(get_emmeans(pwcs[["grupo"]]), ds,
by = c("grupo","Sexo"), suffixes = c(".emms", ""))
ds <- ds[,c("grupo","Sexo","n","mean.score.tde.pre","se.score.tde.pre","mean","se",
"emmean","se.emms","conf.low","conf.high")]
colnames(ds) <- c("grupo","Sexo", "N", paste0(c("M","SE")," (pre)"),
paste0(c("M","SE"), " (unadj)"),
paste0(c("M", "SE"), " (adj)"), "conf.low", "conf.high")
lemms[["grupo:Sexo"]] <- ds
}
if (length(unique(pdat[["Sexo"]])) >= 2) {
wdat = pdat
res = residuals(lm(score.tde.pos ~ score.tde.pre + grupo*Sexo, data = wdat))
non.normal = getNonNormal(res, wdat$id, plimit = 0.05)
wdat = wdat[!wdat$id %in% non.normal,]
wdat.long <- rbind(wdat[,c("id","grupo","Sexo")], wdat[,c("id","grupo","Sexo")])
wdat.long[["time"]] <- c(rep("pre", nrow(wdat)), rep("pos", nrow(wdat)))
wdat.long[["time"]] <- factor(wdat.long[["time"]], c("pre","pos"))
wdat.long[["score.tde"]] <- c(wdat[["score.tde.pre"]], wdat[["score.tde.pos"]])
ldat[["grupo:Sexo"]] = wdat
(non.normal)
}
## [1] "P962" "P1128" "P984" "P1129" "P3637" "P1126" "P1971" "P2995" "P2871"
## [10] "P572" "P921" "P3019" "P2994" "P2880" "P2848" "P2983" "P908" "P3021"
## [19] "P3054" "P1139" "P2858" "P2835" "P2904" "P1117" "P3015" "P2870" "P2929"
## [28] "P2910" "P2886" "P914" "P2913" "P1111" "P2974" "P2964" "P2867" "P2876"
## [37] "P2937" "P1840" "P2973" "P3007" "P2861" "P2969" "P2953" "P2986" "P2883"
## [46] "P2831" "P2975" "P1018" "P3476" "P2997" "P3005" "P1878" "P2866" "P2950"
## [55] "P2993" "P3545" "P2917" "P2978" "P3029" "P2864" "P2888" "P976" "P2854"
## [64] "P2959" "P3548" "P2190" "P929" "P3574" "P2947" "P2845" "P1983" "P3674"
## [73] "P1149" "P1068" "P3475" "P2004" "P2860" "P2982" "P2839" "P3024" "P1885"
## [82] "P2868" "P609" "P2990" "P2946" "P1056" "P2933" "P3020" "P2879" "P873"
## [91] "P1887" "P2865" "P3026" "P3660" "P2956" "P3080" "P3666" "P2846" "P3533"
## [100] "P3228" "P2948" "P2850" "P3000" "P809" "P2905" "P1046" "P1118" "P3221"
## [109] "P1665" "P2903" "P1597" "P2836" "P3537" "P584" "P854" "P1127" "P1804"
## [118] "P2869" "P2979" "P3571" "P1652" "P924" "P1803" "P3088" "P1592" "P2901"
## [127] "P3608" "P848" "P1964" "P2971" "P1900" "P996" "P3732" "P492" "P2922"
## [136] "P859" "P2980" "P1916" "P2832" "P1858" "P1151" "P2375" "P3156" "P3030"
## [145] "P3061" "P2327" "P2894"
if (length(unique(pdat[["Sexo"]])) >= 2) {
aov = anova_test(wdat, score.tde.pos ~ score.tde.pre + grupo*Sexo)
laov[["grupo:Sexo"]] <- merge(get_anova_table(aov), laov[["grupo:Sexo"]],
by="Effect", suffixes = c("","'"))
df = get_anova_table(aov)
}
| Effect | DFn | DFd | F | p | p<.05 | ges |
|---|---|---|---|---|---|---|
| score.tde.pre | 1 | 969 | 5974.401 | 0.000 | * | 0.860 |
| grupo | 1 | 969 | 23.992 | 0.000 | * | 0.024 |
| Sexo | 1 | 969 | 0.058 | 0.810 | 0.000 | |
| grupo:Sexo | 1 | 969 | 0.548 | 0.459 | 0.001 |
if (length(unique(pdat[["Sexo"]])) >= 2) {
pwcs <- list()
pwcs[["Sexo"]] <- emmeans_test(
group_by(wdat, grupo), score.tde.pos ~ Sexo,
covariate = score.tde.pre, p.adjust.method = "bonferroni")
pwcs[["grupo"]] <- emmeans_test(
group_by(wdat, Sexo), score.tde.pos ~ grupo,
covariate = score.tde.pre, p.adjust.method = "bonferroni")
pwc <- plyr::rbind.fill(pwcs[["grupo"]], pwcs[["Sexo"]])
pwc <- pwc[,c("grupo","Sexo", colnames(pwc)[!colnames(pwc) %in% c("grupo","Sexo")])]
}
| grupo | Sexo | term | .y. | group1 | group2 | df | statistic | p | p.adj | p.adj.signif |
|---|---|---|---|---|---|---|---|---|---|---|
| F | score.tde.pre*grupo | score.tde.pos | Controle | Experimental | 969 | -3.977 | 0.000 | 0.000 | **** | |
| M | score.tde.pre*grupo | score.tde.pos | Controle | Experimental | 969 | -2.953 | 0.003 | 0.003 | ** | |
| Controle | score.tde.pre*Sexo | score.tde.pos | F | M | 969 | -0.398 | 0.691 | 0.691 | ns | |
| Experimental | score.tde.pre*Sexo | score.tde.pos | F | M | 969 | 0.663 | 0.507 | 0.507 | ns |
if (length(unique(pdat[["Sexo"]])) >= 2) {
pwc.long <- emmeans_test(dplyr::group_by_at(wdat.long, c("grupo","Sexo")),
score.tde ~ time,
p.adjust.method = "bonferroni")
lpwc[["grupo:Sexo"]] <- merge(plyr::rbind.fill(pwc, pwc.long),
lpwc[["grupo:Sexo"]],
by=c("grupo","Sexo","term",".y.","group1","group2"),
suffixes = c("","'"))
}
| grupo | Sexo | term | .y. | group1 | group2 | df | statistic | p | p.adj | p.adj.signif |
|---|---|---|---|---|---|---|---|---|---|---|
| Controle | F | time | score.tde | pre | pos | 1940 | 1.089 | 0.276 | 0.276 | ns |
| Controle | M | time | score.tde | pre | pos | 1940 | 0.837 | 0.403 | 0.403 | ns |
| Experimental | F | time | score.tde | pre | pos | 1940 | -0.403 | 0.687 | 0.687 | ns |
| Experimental | M | time | score.tde | pre | pos | 1940 | -0.251 | 0.802 | 0.802 | ns |
if (length(unique(pdat[["Sexo"]])) >= 2) {
ds <- get.descriptives(wdat, "score.tde.pos", c("grupo","Sexo"), covar = "score.tde.pre")
ds <- merge(ds[ds$variable != "score.tde.pre",],
ds[ds$variable == "score.tde.pre", !colnames(ds) %in% c("variable")],
by = c("grupo","Sexo"), all.x = T, suffixes = c("", ".score.tde.pre"))
ds <- merge(get_emmeans(pwcs[["grupo"]]), ds,
by = c("grupo","Sexo"), suffixes = c(".emms", ""))
ds <- ds[,c("grupo","Sexo","n","mean.score.tde.pre","se.score.tde.pre",
"mean","se","emmean","se.emms","conf.low","conf.high")]
colnames(ds) <- c("grupo","Sexo", "N", paste0(c("M","SE")," (pre)"),
paste0(c("M","SE"), " (unadj)"),
paste0(c("M", "SE"), " (adj)"), "conf.low", "conf.high")
lemms[["grupo:Sexo"]] <- merge(ds, lemms[["grupo:Sexo"]],
by=c("grupo","Sexo"), suffixes = c("","'"))
}
| grupo | Sexo | N | M (pre) | SE (pre) | M (unadj) | SE (unadj) | M (adj) | SE (adj) | conf.low | conf.high |
|---|---|---|---|---|---|---|---|---|---|---|
| Controle | F | 208 | 40.635 | 1.278 | 38.615 | 1.351 | 35.106 | 0.503 | 34.119 | 36.093 |
| Controle | M | 211 | 33.934 | 1.457 | 32.393 | 1.517 | 35.389 | 0.499 | 34.410 | 36.368 |
| Experimental | F | 276 | 39.623 | 1.053 | 40.272 | 1.123 | 37.744 | 0.436 | 36.889 | 38.600 |
| Experimental | M | 279 | 34.082 | 1.030 | 34.484 | 1.053 | 37.335 | 0.434 | 36.483 | 38.187 |
if (length(unique(pdat[["Sexo"]])) >= 2) {
ggPlotAoC2(pwcs, "grupo", "Sexo", aov, ylab = "Writing (TDE)",
subtitle = which(aov$Effect == "grupo:Sexo"), addParam = "errorbar") +
ggplot2::scale_color_manual(values = color[["Sexo"]]) +
ggplot2::ylab("Writing (TDE)") +
theme(axis.title = element_text(size = 14),
legend.text = element_text(size = 16),
plot.subtitle = element_text(size = 18)) +
if (ymin.ci < ymax.ci) ggplot2::ylim(ymin.ci, ymax.ci)
}
## Scale for colour is already present.
## Adding another scale for colour, which will replace the existing scale.
if (length(unique(pdat[["Sexo"]])) >= 2) {
ggPlotAoC2(pwcs, "Sexo", "grupo", aov, ylab = "Writing (TDE)",
subtitle = which(aov$Effect == "grupo:Sexo"), addParam = "errorbar") +
ggplot2::scale_color_manual(values = color[["grupo"]]) +
ggplot2::ylab("Writing (TDE)") +
theme(axis.title = element_text(size = 14),
legend.text = element_text(size = 16),
plot.subtitle = element_text(size = 18)) +
if (ymin.ci < ymax.ci) ggplot2::ylim(ymin.ci, ymax.ci)
}
## Scale for colour is already present.
## Adding another scale for colour, which will replace the existing scale.
if (length(unique(pdat[["Sexo"]])) >= 2) {
plots <- twoWayAncovaBoxPlots(
wdat, "score.tde.pos", c("grupo","Sexo"), aov, pwcs, covar = "score.tde.pre",
theme = "classic", color = color[["grupo:Sexo"]],
subtitle = which(aov$Effect == "grupo:Sexo"))
}
if (length(unique(pdat[["Sexo"]])) >= 2) {
plots[["grupo:Sexo"]] + ggplot2::ylab("Writing (TDE)") +
ggplot2::scale_x_discrete(labels=c('pre', 'pos')) +
if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}
## Warning: No shared levels found between `names(values)` of the manual scale and the
## data's colour values.
if (length(unique(pdat[["Sexo"]])) >= 2) {
plots <- twoWayAncovaBoxPlots(
wdat.long, "score.tde", c("grupo","Sexo"), aov, pwc.long,
pre.post = "time",
theme = "classic", color = color$prepost)
}
if (length(unique(pdat[["Sexo"]])) >= 2)
plots[["grupo:Sexo"]] + ggplot2::ylab("Writing (TDE)") +
if (ymin < ymax) ggplot2::ylim(ymin, ymax)
if (length(unique(pdat[["Sexo"]])) >= 2) {
ggscatter(wdat, x = "score.tde.pre", y = "score.tde.pos", size = 0.5,
facet.by = c("grupo","Sexo"), add = "reg.line")+
stat_regline_equation(
aes(label = paste(..eq.label.., ..rr.label.., sep = "~~~~"))
) +
ggplot2::xlab("Writing (TDE)") +
ggplot2::ylab("Writing (TDE)") +
theme(axis.title = element_text(size = 14),
legend.text = element_text(size = 16),
plot.subtitle = element_text(size = 18)) +
if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}
if (length(unique(pdat[["Sexo"]])) >= 2) {
ggscatter(wdat, x = "score.tde.pre", y = "score.tde.pos", size = 0.5,
color = "grupo", facet.by = "Sexo", add = "reg.line")+
stat_regline_equation(
aes(label = paste(..eq.label.., ..rr.label.., sep = "~~~~"), color = grupo)
) +
ggplot2::labs(subtitle = rstatix::get_test_label(aov, detailed = T, row = which(aov$Effect == "grupo:Sexo"))) +
ggplot2::scale_color_manual(values = color[["grupo"]]) +
ggplot2::xlab("Writing (TDE)") +
ggplot2::ylab("Writing (TDE)") +
theme(axis.title = element_text(size = 14),
legend.text = element_text(size = 16),
plot.subtitle = element_text(size = 18)) +
if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}
if (length(unique(pdat[["Sexo"]])) >= 2) {
ggscatter(wdat, x = "score.tde.pre", y = "score.tde.pos", size = 0.5,
color = "Sexo", facet.by = "grupo", add = "reg.line")+
stat_regline_equation(
aes(label = paste(..eq.label.., ..rr.label.., sep = "~~~~"), color = Sexo)
) +
ggplot2::labs(subtitle = rstatix::get_test_label(aov, detailed = T, row = which(aov$Effect == "grupo:Sexo"))) +
ggplot2::scale_color_manual(values = color[["Sexo"]]) +
ggplot2::xlab("Writing (TDE)") +
ggplot2::ylab("Writing (TDE)") +
theme(axis.title = element_text(size = 14),
legend.text = element_text(size = 16),
plot.subtitle = element_text(size = 18)) +
if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}
if (length(unique(pdat[["Sexo"]])) >= 2)
res <- augment(lm(score.tde.pos ~ score.tde.pre + grupo*Sexo, data = wdat))
if (length(unique(pdat[["Sexo"]])) >= 2)
shapiro_test(res$.resid)
## # A tibble: 1 × 3
## variable statistic p.value
## <chr> <dbl> <dbl>
## 1 res$.resid 0.997 0.0375
if (length(unique(pdat[["Sexo"]])) >= 2)
levene_test(res, .resid ~ grupo*Sexo)
## # A tibble: 1 × 4
## df1 df2 statistic p
## <int> <int> <dbl> <dbl>
## 1 3 970 0.0813 0.970
pdat = remove_group_data(dat[!is.na(dat[["grupo"]]) & !is.na(dat[["Zona"]]),],
"score.tde.pos", c("grupo","Zona"))
pdat = pdat[pdat[["Zona"]] %in% do.call(
intersect, lapply(unique(pdat[["grupo"]]), FUN = function(x) {
unique(pdat[["Zona"]][which(pdat[["grupo"]] == x)])
})),]
pdat[["grupo"]] = factor(pdat[["grupo"]], level[["grupo"]])
pdat[["Zona"]] = factor(
pdat[["Zona"]],
level[["Zona"]][level[["Zona"]] %in% unique(pdat[["Zona"]])])
pdat.long <- rbind(pdat[,c("id","grupo","Zona")], pdat[,c("id","grupo","Zona")])
pdat.long[["time"]] <- c(rep("pre", nrow(pdat)), rep("pos", nrow(pdat)))
pdat.long[["time"]] <- factor(pdat.long[["time"]], c("pre","pos"))
pdat.long[["score.tde"]] <- c(pdat[["score.tde.pre"]], pdat[["score.tde.pos"]])
if (length(unique(pdat[["Zona"]])) >= 2) {
aov = anova_test(pdat, score.tde.pos ~ score.tde.pre + grupo*Zona)
laov[["grupo:Zona"]] <- get_anova_table(aov)
}
if (length(unique(pdat[["Zona"]])) >= 2) {
pwcs <- list()
pwcs[["Zona"]] <- emmeans_test(
group_by(pdat, grupo), score.tde.pos ~ Zona,
covariate = score.tde.pre, p.adjust.method = "bonferroni")
pwcs[["grupo"]] <- emmeans_test(
group_by(pdat, Zona), score.tde.pos ~ grupo,
covariate = score.tde.pre, p.adjust.method = "bonferroni")
pwc <- plyr::rbind.fill(pwcs[["grupo"]], pwcs[["Zona"]])
pwc <- pwc[,c("grupo","Zona", colnames(pwc)[!colnames(pwc) %in% c("grupo","Zona")])]
}
if (length(unique(pdat[["Zona"]])) >= 2) {
pwc.long <- emmeans_test(dplyr::group_by_at(pdat.long, c("grupo","Zona")),
score.tde ~ time,
p.adjust.method = "bonferroni")
lpwc[["grupo:Zona"]] <- plyr::rbind.fill(pwc, pwc.long)
}
if (length(unique(pdat[["Zona"]])) >= 2) {
ds <- get.descriptives(pdat, "score.tde.pos", c("grupo","Zona"), covar = "score.tde.pre")
ds <- merge(ds[ds$variable != "score.tde.pre",],
ds[ds$variable == "score.tde.pre", !colnames(ds) %in% c("variable")],
by = c("grupo","Zona"), all.x = T, suffixes = c("", ".score.tde.pre"))
ds <- merge(get_emmeans(pwcs[["grupo"]]), ds,
by = c("grupo","Zona"), suffixes = c(".emms", ""))
ds <- ds[,c("grupo","Zona","n","mean.score.tde.pre","se.score.tde.pre","mean","se",
"emmean","se.emms","conf.low","conf.high")]
colnames(ds) <- c("grupo","Zona", "N", paste0(c("M","SE")," (pre)"),
paste0(c("M","SE"), " (unadj)"),
paste0(c("M", "SE"), " (adj)"), "conf.low", "conf.high")
lemms[["grupo:Zona"]] <- ds
}
if (length(unique(pdat[["Zona"]])) >= 2) {
wdat = pdat
res = residuals(lm(score.tde.pos ~ score.tde.pre + grupo*Zona, data = wdat))
non.normal = getNonNormal(res, wdat$id, plimit = 0.05)
wdat = wdat[!wdat$id %in% non.normal,]
wdat.long <- rbind(wdat[,c("id","grupo","Zona")], wdat[,c("id","grupo","Zona")])
wdat.long[["time"]] <- c(rep("pre", nrow(wdat)), rep("pos", nrow(wdat)))
wdat.long[["time"]] <- factor(wdat.long[["time"]], c("pre","pos"))
wdat.long[["score.tde"]] <- c(wdat[["score.tde.pre"]], wdat[["score.tde.pos"]])
ldat[["grupo:Zona"]] = wdat
(non.normal)
}
## [1] "P962" "P984" "P1971" "P2929" "P1117" "P2848" "P2917" "P2870" "P2871"
## [10] "P2835" "P921" "P2959" "P3029" "P1139" "P572" "P2983" "P2858" "P3021"
## [19] "P3080" "P606" "P2933" "P914" "P2831" "P2946" "P3533" "P2953" "P2886"
## [28] "P3548" "P3476" "P2861" "P2880" "P2982" "P2995" "P3674" "P2864" "P2883"
## [37] "P2950" "P2004" "P3475" "P3012" "P3010" "P3015" "P2975" "P2937" "P3660"
## [46] "P2910" "P1691" "P2868" "P2860" "P1878" "P609" "P908" "P2997" "P2956"
## [55] "P2973" "P2879" "P2854" "P3024" "P2967" "P2948" "P2909" "P1056" "P2964"
if (length(unique(pdat[["Zona"]])) >= 2) {
aov = anova_test(wdat, score.tde.pos ~ score.tde.pre + grupo*Zona)
laov[["grupo:Zona"]] <- merge(get_anova_table(aov), laov[["grupo:Zona"]],
by="Effect", suffixes = c("","'"))
df = get_anova_table(aov)
}
| Effect | DFn | DFd | F | p | p<.05 | ges |
|---|---|---|---|---|---|---|
| score.tde.pre | 1 | 735 | 3559.226 | 0 | * | 0.829 |
| grupo | 1 | 735 | 26.138 | 0 | * | 0.034 |
| Zona | 1 | 735 | 54.679 | 0 | * | 0.069 |
| grupo:Zona | 1 | 735 | 14.155 | 0 | * | 0.019 |
if (length(unique(pdat[["Zona"]])) >= 2) {
pwcs <- list()
pwcs[["Zona"]] <- emmeans_test(
group_by(wdat, grupo), score.tde.pos ~ Zona,
covariate = score.tde.pre, p.adjust.method = "bonferroni")
pwcs[["grupo"]] <- emmeans_test(
group_by(wdat, Zona), score.tde.pos ~ grupo,
covariate = score.tde.pre, p.adjust.method = "bonferroni")
pwc <- plyr::rbind.fill(pwcs[["grupo"]], pwcs[["Zona"]])
pwc <- pwc[,c("grupo","Zona", colnames(pwc)[!colnames(pwc) %in% c("grupo","Zona")])]
}
| grupo | Zona | term | .y. | group1 | group2 | df | statistic | p | p.adj | p.adj.signif |
|---|---|---|---|---|---|---|---|---|---|---|
| Rural | score.tde.pre*grupo | score.tde.pos | Controle | Experimental | 735 | -2.009 | 0.045 | 0.045 | * | |
| Urbana | score.tde.pre*grupo | score.tde.pos | Controle | Experimental | 735 | -6.023 | 0.000 | 0.000 | **** | |
| Controle | score.tde.pre*Zona | score.tde.pos | Rural | Urbana | 735 | 7.675 | 0.000 | 0.000 | **** | |
| Experimental | score.tde.pre*Zona | score.tde.pos | Rural | Urbana | 735 | 3.188 | 0.001 | 0.001 | ** |
if (length(unique(pdat[["Zona"]])) >= 2) {
pwc.long <- emmeans_test(dplyr::group_by_at(wdat.long, c("grupo","Zona")),
score.tde ~ time,
p.adjust.method = "bonferroni")
lpwc[["grupo:Zona"]] <- merge(plyr::rbind.fill(pwc, pwc.long),
lpwc[["grupo:Zona"]],
by=c("grupo","Zona","term",".y.","group1","group2"),
suffixes = c("","'"))
}
| grupo | Zona | term | .y. | group1 | group2 | df | statistic | p | p.adj | p.adj.signif |
|---|---|---|---|---|---|---|---|---|---|---|
| Controle | Rural | time | score.tde | pre | pos | 1472 | 0.543 | 0.588 | 0.588 | ns |
| Controle | Urbana | time | score.tde | pre | pos | 1472 | 3.191 | 0.001 | 0.001 | ** |
| Experimental | Rural | time | score.tde | pre | pos | 1472 | -0.333 | 0.739 | 0.739 | ns |
| Experimental | Urbana | time | score.tde | pre | pos | 1472 | 1.001 | 0.317 | 0.317 | ns |
if (length(unique(pdat[["Zona"]])) >= 2) {
ds <- get.descriptives(wdat, "score.tde.pos", c("grupo","Zona"), covar = "score.tde.pre")
ds <- merge(ds[ds$variable != "score.tde.pre",],
ds[ds$variable == "score.tde.pre", !colnames(ds) %in% c("variable")],
by = c("grupo","Zona"), all.x = T, suffixes = c("", ".score.tde.pre"))
ds <- merge(get_emmeans(pwcs[["grupo"]]), ds,
by = c("grupo","Zona"), suffixes = c(".emms", ""))
ds <- ds[,c("grupo","Zona","n","mean.score.tde.pre","se.score.tde.pre",
"mean","se","emmean","se.emms","conf.low","conf.high")]
colnames(ds) <- c("grupo","Zona", "N", paste0(c("M","SE")," (pre)"),
paste0(c("M","SE"), " (unadj)"),
paste0(c("M", "SE"), " (adj)"), "conf.low", "conf.high")
lemms[["grupo:Zona"]] <- merge(ds, lemms[["grupo:Zona"]],
by=c("grupo","Zona"), suffixes = c("","'"))
}
| grupo | Zona | N | M (pre) | SE (pre) | M (unadj) | SE (unadj) | M (adj) | SE (adj) | conf.low | conf.high |
|---|---|---|---|---|---|---|---|---|---|---|
| Controle | Rural | 228 | 35.956 | 1.330 | 34.978 | 1.426 | 35.358 | 0.547 | 34.284 | 36.432 |
| Controle | Urbana | 101 | 39.743 | 1.823 | 31.099 | 2.044 | 27.763 | 0.824 | 26.145 | 29.380 |
| Experimental | Rural | 260 | 34.215 | 1.113 | 34.777 | 1.186 | 36.865 | 0.514 | 35.857 | 37.874 |
| Experimental | Urbana | 151 | 38.318 | 1.389 | 36.099 | 1.501 | 34.161 | 0.673 | 32.840 | 35.483 |
if (length(unique(pdat[["Zona"]])) >= 2) {
ggPlotAoC2(pwcs, "grupo", "Zona", aov, ylab = "Writing (TDE)",
subtitle = which(aov$Effect == "grupo:Zona"), addParam = "errorbar") +
ggplot2::scale_color_manual(values = color[["Zona"]]) +
ggplot2::ylab("Writing (TDE)") +
theme(axis.title = element_text(size = 14),
legend.text = element_text(size = 16),
plot.subtitle = element_text(size = 18)) +
if (ymin.ci < ymax.ci) ggplot2::ylim(ymin.ci, ymax.ci)
}
## Scale for colour is already present.
## Adding another scale for colour, which will replace the existing scale.
if (length(unique(pdat[["Zona"]])) >= 2) {
ggPlotAoC2(pwcs, "Zona", "grupo", aov, ylab = "Writing (TDE)",
subtitle = which(aov$Effect == "grupo:Zona"), addParam = "errorbar") +
ggplot2::scale_color_manual(values = color[["grupo"]]) +
ggplot2::ylab("Writing (TDE)") +
theme(axis.title = element_text(size = 14),
legend.text = element_text(size = 16),
plot.subtitle = element_text(size = 18)) +
if (ymin.ci < ymax.ci) ggplot2::ylim(ymin.ci, ymax.ci)
}
## Scale for colour is already present.
## Adding another scale for colour, which will replace the existing scale.
if (length(unique(pdat[["Zona"]])) >= 2) {
plots <- twoWayAncovaBoxPlots(
wdat, "score.tde.pos", c("grupo","Zona"), aov, pwcs, covar = "score.tde.pre",
theme = "classic", color = color[["grupo:Zona"]],
subtitle = which(aov$Effect == "grupo:Zona"))
}
if (length(unique(pdat[["Zona"]])) >= 2) {
plots[["grupo:Zona"]] + ggplot2::ylab("Writing (TDE)") +
ggplot2::scale_x_discrete(labels=c('pre', 'pos')) +
if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}
## Warning: No shared levels found between `names(values)` of the manual scale and the
## data's colour values.
if (length(unique(pdat[["Zona"]])) >= 2) {
plots <- twoWayAncovaBoxPlots(
wdat.long, "score.tde", c("grupo","Zona"), aov, pwc.long,
pre.post = "time",
theme = "classic", color = color$prepost)
}
if (length(unique(pdat[["Zona"]])) >= 2)
plots[["grupo:Zona"]] + ggplot2::ylab("Writing (TDE)") +
if (ymin < ymax) ggplot2::ylim(ymin, ymax)
if (length(unique(pdat[["Zona"]])) >= 2) {
ggscatter(wdat, x = "score.tde.pre", y = "score.tde.pos", size = 0.5,
facet.by = c("grupo","Zona"), add = "reg.line")+
stat_regline_equation(
aes(label = paste(..eq.label.., ..rr.label.., sep = "~~~~"))
) +
ggplot2::xlab("Writing (TDE)") +
ggplot2::ylab("Writing (TDE)") +
theme(axis.title = element_text(size = 14),
legend.text = element_text(size = 16),
plot.subtitle = element_text(size = 18)) +
if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}
if (length(unique(pdat[["Zona"]])) >= 2) {
ggscatter(wdat, x = "score.tde.pre", y = "score.tde.pos", size = 0.5,
color = "grupo", facet.by = "Zona", add = "reg.line")+
stat_regline_equation(
aes(label = paste(..eq.label.., ..rr.label.., sep = "~~~~"), color = grupo)
) +
ggplot2::labs(subtitle = rstatix::get_test_label(aov, detailed = T, row = which(aov$Effect == "grupo:Zona"))) +
ggplot2::scale_color_manual(values = color[["grupo"]]) +
ggplot2::xlab("Writing (TDE)") +
ggplot2::ylab("Writing (TDE)") +
theme(axis.title = element_text(size = 14),
legend.text = element_text(size = 16),
plot.subtitle = element_text(size = 18)) +
if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}
if (length(unique(pdat[["Zona"]])) >= 2) {
ggscatter(wdat, x = "score.tde.pre", y = "score.tde.pos", size = 0.5,
color = "Zona", facet.by = "grupo", add = "reg.line")+
stat_regline_equation(
aes(label = paste(..eq.label.., ..rr.label.., sep = "~~~~"), color = Zona)
) +
ggplot2::labs(subtitle = rstatix::get_test_label(aov, detailed = T, row = which(aov$Effect == "grupo:Zona"))) +
ggplot2::scale_color_manual(values = color[["Zona"]]) +
ggplot2::xlab("Writing (TDE)") +
ggplot2::ylab("Writing (TDE)") +
theme(axis.title = element_text(size = 14),
legend.text = element_text(size = 16),
plot.subtitle = element_text(size = 18)) +
if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}
if (length(unique(pdat[["Zona"]])) >= 2)
res <- augment(lm(score.tde.pos ~ score.tde.pre + grupo*Zona, data = wdat))
if (length(unique(pdat[["Zona"]])) >= 2)
shapiro_test(res$.resid)
## # A tibble: 1 × 3
## variable statistic p.value
## <chr> <dbl> <dbl>
## 1 res$.resid 0.995 0.0253
if (length(unique(pdat[["Zona"]])) >= 2)
levene_test(res, .resid ~ grupo*Zona)
## # A tibble: 1 × 4
## df1 df2 statistic p
## <int> <int> <dbl> <dbl>
## 1 3 736 2.40 0.0667
pdat = remove_group_data(dat[!is.na(dat[["grupo"]]) & !is.na(dat[["Cor.Raca"]]),],
"score.tde.pos", c("grupo","Cor.Raca"))
## Warning: There was 1 warning in `mutate()`.
## ℹ In argument: `ci = abs(stats::qt(alpha/2, .data$n - 1) * .data$se)`.
## Caused by warning:
## ! There was 1 warning in `mutate()`.
## ℹ In argument: `ci = abs(stats::qt(alpha/2, .data$n - 1) * .data$se)`.
## Caused by warning in `stats::qt()`:
## ! NaNs produced
pdat = pdat[pdat[["Cor.Raca"]] %in% do.call(
intersect, lapply(unique(pdat[["grupo"]]), FUN = function(x) {
unique(pdat[["Cor.Raca"]][which(pdat[["grupo"]] == x)])
})),]
pdat[["grupo"]] = factor(pdat[["grupo"]], level[["grupo"]])
pdat[["Cor.Raca"]] = factor(
pdat[["Cor.Raca"]],
level[["Cor.Raca"]][level[["Cor.Raca"]] %in% unique(pdat[["Cor.Raca"]])])
pdat.long <- rbind(pdat[,c("id","grupo","Cor.Raca")], pdat[,c("id","grupo","Cor.Raca")])
pdat.long[["time"]] <- c(rep("pre", nrow(pdat)), rep("pos", nrow(pdat)))
pdat.long[["time"]] <- factor(pdat.long[["time"]], c("pre","pos"))
pdat.long[["score.tde"]] <- c(pdat[["score.tde.pre"]], pdat[["score.tde.pos"]])
if (length(unique(pdat[["Cor.Raca"]])) >= 2) {
aov = anova_test(pdat, score.tde.pos ~ score.tde.pre + grupo*Cor.Raca)
laov[["grupo:Cor.Raca"]] <- get_anova_table(aov)
}
if (length(unique(pdat[["Cor.Raca"]])) >= 2) {
pwcs <- list()
pwcs[["Cor.Raca"]] <- emmeans_test(
group_by(pdat, grupo), score.tde.pos ~ Cor.Raca,
covariate = score.tde.pre, p.adjust.method = "bonferroni")
pwcs[["grupo"]] <- emmeans_test(
group_by(pdat, Cor.Raca), score.tde.pos ~ grupo,
covariate = score.tde.pre, p.adjust.method = "bonferroni")
pwc <- plyr::rbind.fill(pwcs[["grupo"]], pwcs[["Cor.Raca"]])
pwc <- pwc[,c("grupo","Cor.Raca", colnames(pwc)[!colnames(pwc) %in% c("grupo","Cor.Raca")])]
}
if (length(unique(pdat[["Cor.Raca"]])) >= 2) {
pwc.long <- emmeans_test(dplyr::group_by_at(pdat.long, c("grupo","Cor.Raca")),
score.tde ~ time,
p.adjust.method = "bonferroni")
lpwc[["grupo:Cor.Raca"]] <- plyr::rbind.fill(pwc, pwc.long)
}
if (length(unique(pdat[["Cor.Raca"]])) >= 2) {
ds <- get.descriptives(pdat, "score.tde.pos", c("grupo","Cor.Raca"), covar = "score.tde.pre")
ds <- merge(ds[ds$variable != "score.tde.pre",],
ds[ds$variable == "score.tde.pre", !colnames(ds) %in% c("variable")],
by = c("grupo","Cor.Raca"), all.x = T, suffixes = c("", ".score.tde.pre"))
ds <- merge(get_emmeans(pwcs[["grupo"]]), ds,
by = c("grupo","Cor.Raca"), suffixes = c(".emms", ""))
ds <- ds[,c("grupo","Cor.Raca","n","mean.score.tde.pre","se.score.tde.pre","mean","se",
"emmean","se.emms","conf.low","conf.high")]
colnames(ds) <- c("grupo","Cor.Raca", "N", paste0(c("M","SE")," (pre)"),
paste0(c("M","SE"), " (unadj)"),
paste0(c("M", "SE"), " (adj)"), "conf.low", "conf.high")
lemms[["grupo:Cor.Raca"]] <- ds
}
if (length(unique(pdat[["Cor.Raca"]])) >= 2) {
wdat = pdat
res = residuals(lm(score.tde.pos ~ score.tde.pre + grupo*Cor.Raca, data = wdat))
non.normal = getNonNormal(res, wdat$id, plimit = 0.05)
wdat = wdat[!wdat$id %in% non.normal,]
wdat.long <- rbind(wdat[,c("id","grupo","Cor.Raca")], wdat[,c("id","grupo","Cor.Raca")])
wdat.long[["time"]] <- c(rep("pre", nrow(wdat)), rep("pos", nrow(wdat)))
wdat.long[["time"]] <- factor(wdat.long[["time"]], c("pre","pos"))
wdat.long[["score.tde"]] <- c(wdat[["score.tde.pre"]], wdat[["score.tde.pos"]])
ldat[["grupo:Cor.Raca"]] = wdat
(non.normal)
}
## [1] "P1128" "P1126" "P908" "P2995" "P1139" "P3021" "P2871" "P2858" "P3637"
## [10] "P2870" "P1117" "P572" "P2978" "P2975" "P2983" "P2904" "P2835" "P3000"
## [19] "P2888" "P2993" "P2905" "P1118" "P1804" "P3007" "P3228" "P3029" "P2865"
## [28] "P2967" "P1018" "P2994" "P2953" "P2997" "P3476" "P3054" "P606"
if (length(unique(pdat[["Cor.Raca"]])) >= 2) {
aov = anova_test(wdat, score.tde.pos ~ score.tde.pre + grupo*Cor.Raca)
laov[["grupo:Cor.Raca"]] <- merge(get_anova_table(aov), laov[["grupo:Cor.Raca"]],
by="Effect", suffixes = c("","'"))
df = get_anova_table(aov)
}
| Effect | DFn | DFd | F | p | p<.05 | ges |
|---|---|---|---|---|---|---|
| score.tde.pre | 1 | 447 | 1620.497 | 0.000 | * | 0.784 |
| grupo | 1 | 447 | 7.311 | 0.007 | * | 0.016 |
| Cor.Raca | 2 | 447 | 3.357 | 0.036 | * | 0.015 |
| grupo:Cor.Raca | 2 | 447 | 1.174 | 0.310 | 0.005 |
if (length(unique(pdat[["Cor.Raca"]])) >= 2) {
pwcs <- list()
pwcs[["Cor.Raca"]] <- emmeans_test(
group_by(wdat, grupo), score.tde.pos ~ Cor.Raca,
covariate = score.tde.pre, p.adjust.method = "bonferroni")
pwcs[["grupo"]] <- emmeans_test(
group_by(wdat, Cor.Raca), score.tde.pos ~ grupo,
covariate = score.tde.pre, p.adjust.method = "bonferroni")
pwc <- plyr::rbind.fill(pwcs[["grupo"]], pwcs[["Cor.Raca"]])
pwc <- pwc[,c("grupo","Cor.Raca", colnames(pwc)[!colnames(pwc) %in% c("grupo","Cor.Raca")])]
}
| grupo | Cor.Raca | term | .y. | group1 | group2 | df | statistic | p | p.adj | p.adj.signif |
|---|---|---|---|---|---|---|---|---|---|---|
| Parda | score.tde.pre*grupo | score.tde.pos | Controle | Experimental | 447 | -1.911 | 0.057 | 0.057 | ns | |
| Indígena | score.tde.pre*grupo | score.tde.pos | Controle | Experimental | 447 | 0.274 | 0.784 | 0.784 | ns | |
| Branca | score.tde.pre*grupo | score.tde.pos | Controle | Experimental | 447 | -2.442 | 0.015 | 0.015 | * | |
| Controle | score.tde.pre*Cor.Raca | score.tde.pos | Parda | Indígena | 447 | -2.163 | 0.031 | 0.093 | ns | |
| Controle | score.tde.pre*Cor.Raca | score.tde.pos | Parda | Branca | 447 | 1.334 | 0.183 | 0.549 | ns | |
| Controle | score.tde.pre*Cor.Raca | score.tde.pos | Indígena | Branca | 447 | 2.687 | 0.007 | 0.022 | * | |
| Experimental | score.tde.pre*Cor.Raca | score.tde.pos | Parda | Indígena | 447 | -1.314 | 0.190 | 0.569 | ns | |
| Experimental | score.tde.pre*Cor.Raca | score.tde.pos | Parda | Branca | 447 | -0.308 | 0.759 | 1.000 | ns | |
| Experimental | score.tde.pre*Cor.Raca | score.tde.pos | Indígena | Branca | 447 | 1.060 | 0.290 | 0.870 | ns |
if (length(unique(pdat[["Cor.Raca"]])) >= 2) {
pwc.long <- emmeans_test(dplyr::group_by_at(wdat.long, c("grupo","Cor.Raca")),
score.tde ~ time,
p.adjust.method = "bonferroni")
lpwc[["grupo:Cor.Raca"]] <- merge(plyr::rbind.fill(pwc, pwc.long),
lpwc[["grupo:Cor.Raca"]],
by=c("grupo","Cor.Raca","term",".y.","group1","group2"),
suffixes = c("","'"))
}
| grupo | Cor.Raca | term | .y. | group1 | group2 | df | statistic | p | p.adj | p.adj.signif |
|---|---|---|---|---|---|---|---|---|---|---|
| Controle | Parda | time | score.tde | pre | pos | 896 | 1.090 | 0.276 | 0.276 | ns |
| Controle | Indígena | time | score.tde | pre | pos | 896 | -0.441 | 0.659 | 0.659 | ns |
| Controle | Branca | time | score.tde | pre | pos | 896 | 1.172 | 0.241 | 0.241 | ns |
| Experimental | Parda | time | score.tde | pre | pos | 896 | 0.163 | 0.870 | 0.870 | ns |
| Experimental | Indígena | time | score.tde | pre | pos | 896 | -0.463 | 0.644 | 0.644 | ns |
| Experimental | Branca | time | score.tde | pre | pos | 896 | -0.019 | 0.985 | 0.985 | ns |
if (length(unique(pdat[["Cor.Raca"]])) >= 2) {
ds <- get.descriptives(wdat, "score.tde.pos", c("grupo","Cor.Raca"), covar = "score.tde.pre")
ds <- merge(ds[ds$variable != "score.tde.pre",],
ds[ds$variable == "score.tde.pre", !colnames(ds) %in% c("variable")],
by = c("grupo","Cor.Raca"), all.x = T, suffixes = c("", ".score.tde.pre"))
ds <- merge(get_emmeans(pwcs[["grupo"]]), ds,
by = c("grupo","Cor.Raca"), suffixes = c(".emms", ""))
ds <- ds[,c("grupo","Cor.Raca","n","mean.score.tde.pre","se.score.tde.pre",
"mean","se","emmean","se.emms","conf.low","conf.high")]
colnames(ds) <- c("grupo","Cor.Raca", "N", paste0(c("M","SE")," (pre)"),
paste0(c("M","SE"), " (unadj)"),
paste0(c("M", "SE"), " (adj)"), "conf.low", "conf.high")
lemms[["grupo:Cor.Raca"]] <- merge(ds, lemms[["grupo:Cor.Raca"]],
by=c("grupo","Cor.Raca"), suffixes = c("","'"))
}
| grupo | Cor.Raca | N | M (pre) | SE (pre) | M (unadj) | SE (unadj) | M (adj) | SE (adj) | conf.low | conf.high |
|---|---|---|---|---|---|---|---|---|---|---|
| Controle | Branca | 45 | 41.378 | 2.626 | 36.600 | 3.007 | 30.951 | 1.399 | 28.202 | 33.701 |
| Controle | Indígena | 11 | 42.000 | 5.215 | 45.636 | 6.009 | 39.393 | 2.820 | 33.851 | 44.935 |
| Controle | Parda | 150 | 36.320 | 1.578 | 33.887 | 1.695 | 33.075 | 0.763 | 31.576 | 34.574 |
| Experimental | Branca | 58 | 34.517 | 2.651 | 34.586 | 2.746 | 35.499 | 1.226 | 33.088 | 37.909 |
| Experimental | Indígena | 15 | 27.067 | 4.406 | 30.333 | 4.574 | 38.371 | 2.420 | 33.616 | 43.126 |
| Experimental | Parda | 175 | 33.851 | 1.343 | 33.514 | 1.460 | 35.064 | 0.707 | 33.674 | 36.453 |
if (length(unique(pdat[["Cor.Raca"]])) >= 2) {
ggPlotAoC2(pwcs, "grupo", "Cor.Raca", aov, ylab = "Writing (TDE)",
subtitle = which(aov$Effect == "grupo:Cor.Raca"), addParam = "errorbar") +
ggplot2::scale_color_manual(values = color[["Cor.Raca"]]) +
ggplot2::ylab("Writing (TDE)") +
theme(axis.title = element_text(size = 14),
legend.text = element_text(size = 16),
plot.subtitle = element_text(size = 18)) +
if (ymin.ci < ymax.ci) ggplot2::ylim(ymin.ci, ymax.ci)
}
## Scale for colour is already present.
## Adding another scale for colour, which will replace the existing scale.
if (length(unique(pdat[["Cor.Raca"]])) >= 2) {
ggPlotAoC2(pwcs, "Cor.Raca", "grupo", aov, ylab = "Writing (TDE)",
subtitle = which(aov$Effect == "grupo:Cor.Raca"), addParam = "errorbar") +
ggplot2::scale_color_manual(values = color[["grupo"]]) +
ggplot2::ylab("Writing (TDE)") +
theme(axis.title = element_text(size = 14),
legend.text = element_text(size = 16),
plot.subtitle = element_text(size = 18)) +
if (ymin.ci < ymax.ci) ggplot2::ylim(ymin.ci, ymax.ci)
}
## Scale for colour is already present.
## Adding another scale for colour, which will replace the existing scale.
if (length(unique(pdat[["Cor.Raca"]])) >= 2) {
plots <- twoWayAncovaBoxPlots(
wdat, "score.tde.pos", c("grupo","Cor.Raca"), aov, pwcs, covar = "score.tde.pre",
theme = "classic", color = color[["grupo:Cor.Raca"]],
subtitle = which(aov$Effect == "grupo:Cor.Raca"))
}
if (length(unique(pdat[["Cor.Raca"]])) >= 2) {
plots[["grupo:Cor.Raca"]] + ggplot2::ylab("Writing (TDE)") +
ggplot2::scale_x_discrete(labels=c('pre', 'pos')) +
if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}
## Warning: No shared levels found between `names(values)` of the manual scale and the
## data's colour values.
if (length(unique(pdat[["Cor.Raca"]])) >= 2) {
plots <- twoWayAncovaBoxPlots(
wdat.long, "score.tde", c("grupo","Cor.Raca"), aov, pwc.long,
pre.post = "time",
theme = "classic", color = color$prepost)
}
if (length(unique(pdat[["Cor.Raca"]])) >= 2)
plots[["grupo:Cor.Raca"]] + ggplot2::ylab("Writing (TDE)") +
if (ymin < ymax) ggplot2::ylim(ymin, ymax)
if (length(unique(pdat[["Cor.Raca"]])) >= 2) {
ggscatter(wdat, x = "score.tde.pre", y = "score.tde.pos", size = 0.5,
facet.by = c("grupo","Cor.Raca"), add = "reg.line")+
stat_regline_equation(
aes(label = paste(..eq.label.., ..rr.label.., sep = "~~~~"))
) +
ggplot2::xlab("Writing (TDE)") +
ggplot2::ylab("Writing (TDE)") +
theme(axis.title = element_text(size = 14),
legend.text = element_text(size = 16),
plot.subtitle = element_text(size = 18)) +
if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}
if (length(unique(pdat[["Cor.Raca"]])) >= 2) {
ggscatter(wdat, x = "score.tde.pre", y = "score.tde.pos", size = 0.5,
color = "grupo", facet.by = "Cor.Raca", add = "reg.line")+
stat_regline_equation(
aes(label = paste(..eq.label.., ..rr.label.., sep = "~~~~"), color = grupo)
) +
ggplot2::labs(subtitle = rstatix::get_test_label(aov, detailed = T, row = which(aov$Effect == "grupo:Cor.Raca"))) +
ggplot2::scale_color_manual(values = color[["grupo"]]) +
ggplot2::xlab("Writing (TDE)") +
ggplot2::ylab("Writing (TDE)") +
theme(axis.title = element_text(size = 14),
legend.text = element_text(size = 16),
plot.subtitle = element_text(size = 18)) +
if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}
if (length(unique(pdat[["Cor.Raca"]])) >= 2) {
ggscatter(wdat, x = "score.tde.pre", y = "score.tde.pos", size = 0.5,
color = "Cor.Raca", facet.by = "grupo", add = "reg.line")+
stat_regline_equation(
aes(label = paste(..eq.label.., ..rr.label.., sep = "~~~~"), color = Cor.Raca)
) +
ggplot2::labs(subtitle = rstatix::get_test_label(aov, detailed = T, row = which(aov$Effect == "grupo:Cor.Raca"))) +
ggplot2::scale_color_manual(values = color[["Cor.Raca"]]) +
ggplot2::xlab("Writing (TDE)") +
ggplot2::ylab("Writing (TDE)") +
theme(axis.title = element_text(size = 14),
legend.text = element_text(size = 16),
plot.subtitle = element_text(size = 18)) +
if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}
if (length(unique(pdat[["Cor.Raca"]])) >= 2)
res <- augment(lm(score.tde.pos ~ score.tde.pre + grupo*Cor.Raca, data = wdat))
if (length(unique(pdat[["Cor.Raca"]])) >= 2)
shapiro_test(res$.resid)
## # A tibble: 1 × 3
## variable statistic p.value
## <chr> <dbl> <dbl>
## 1 res$.resid 0.992 0.0140
if (length(unique(pdat[["Cor.Raca"]])) >= 2)
levene_test(res, .resid ~ grupo*Cor.Raca)
## # A tibble: 1 × 4
## df1 df2 statistic p
## <int> <int> <dbl> <dbl>
## 1 5 448 0.202 0.962
pdat = remove_group_data(dat[!is.na(dat[["grupo"]]) & !is.na(dat[["Serie"]]),],
"score.tde.pos", c("grupo","Serie"))
pdat = pdat[pdat[["Serie"]] %in% do.call(
intersect, lapply(unique(pdat[["grupo"]]), FUN = function(x) {
unique(pdat[["Serie"]][which(pdat[["grupo"]] == x)])
})),]
pdat[["grupo"]] = factor(pdat[["grupo"]], level[["grupo"]])
pdat[["Serie"]] = factor(
pdat[["Serie"]],
level[["Serie"]][level[["Serie"]] %in% unique(pdat[["Serie"]])])
pdat.long <- rbind(pdat[,c("id","grupo","Serie")], pdat[,c("id","grupo","Serie")])
pdat.long[["time"]] <- c(rep("pre", nrow(pdat)), rep("pos", nrow(pdat)))
pdat.long[["time"]] <- factor(pdat.long[["time"]], c("pre","pos"))
pdat.long[["score.tde"]] <- c(pdat[["score.tde.pre"]], pdat[["score.tde.pos"]])
if (length(unique(pdat[["Serie"]])) >= 2) {
aov = anova_test(pdat, score.tde.pos ~ score.tde.pre + grupo*Serie)
laov[["grupo:Serie"]] <- get_anova_table(aov)
}
if (length(unique(pdat[["Serie"]])) >= 2) {
pwcs <- list()
pwcs[["Serie"]] <- emmeans_test(
group_by(pdat, grupo), score.tde.pos ~ Serie,
covariate = score.tde.pre, p.adjust.method = "bonferroni")
pwcs[["grupo"]] <- emmeans_test(
group_by(pdat, Serie), score.tde.pos ~ grupo,
covariate = score.tde.pre, p.adjust.method = "bonferroni")
pwc <- plyr::rbind.fill(pwcs[["grupo"]], pwcs[["Serie"]])
pwc <- pwc[,c("grupo","Serie", colnames(pwc)[!colnames(pwc) %in% c("grupo","Serie")])]
}
if (length(unique(pdat[["Serie"]])) >= 2) {
pwc.long <- emmeans_test(dplyr::group_by_at(pdat.long, c("grupo","Serie")),
score.tde ~ time,
p.adjust.method = "bonferroni")
lpwc[["grupo:Serie"]] <- plyr::rbind.fill(pwc, pwc.long)
}
if (length(unique(pdat[["Serie"]])) >= 2) {
ds <- get.descriptives(pdat, "score.tde.pos", c("grupo","Serie"), covar = "score.tde.pre")
ds <- merge(ds[ds$variable != "score.tde.pre",],
ds[ds$variable == "score.tde.pre", !colnames(ds) %in% c("variable")],
by = c("grupo","Serie"), all.x = T, suffixes = c("", ".score.tde.pre"))
ds <- merge(get_emmeans(pwcs[["grupo"]]), ds,
by = c("grupo","Serie"), suffixes = c(".emms", ""))
ds <- ds[,c("grupo","Serie","n","mean.score.tde.pre","se.score.tde.pre","mean","se",
"emmean","se.emms","conf.low","conf.high")]
colnames(ds) <- c("grupo","Serie", "N", paste0(c("M","SE")," (pre)"),
paste0(c("M","SE"), " (unadj)"),
paste0(c("M", "SE"), " (adj)"), "conf.low", "conf.high")
lemms[["grupo:Serie"]] <- ds
}
if (length(unique(pdat[["Serie"]])) >= 2) {
wdat = pdat
res = residuals(lm(score.tde.pos ~ score.tde.pre + grupo*Serie, data = wdat))
non.normal = getNonNormal(res, wdat$id, plimit = 0.05)
wdat = wdat[!wdat$id %in% non.normal,]
wdat.long <- rbind(wdat[,c("id","grupo","Serie")], wdat[,c("id","grupo","Serie")])
wdat.long[["time"]] <- c(rep("pre", nrow(wdat)), rep("pos", nrow(wdat)))
wdat.long[["time"]] <- factor(wdat.long[["time"]], c("pre","pos"))
wdat.long[["score.tde"]] <- c(wdat[["score.tde.pre"]], wdat[["score.tde.pos"]])
ldat[["grupo:Serie"]] = wdat
(non.normal)
}
## [1] "P962" "P1128" "P984" "P1129" "P1971" "P1126" "P1139" "P2835" "P2983"
## [10] "P572" "P1117" "P3571" "P3537" "P3574" "P1983" "P2848" "P809" "P3637"
## [19] "P2910" "P976" "P2870" "P2969" "P2866" "P3732" "P2913" "P921" "P1018"
## [28] "P2964" "P1111" "P2967" "P3228" "P929" "P2959" "P2886" "P914" "P2995"
## [37] "P2982" "P2375" "P3241" "P2975" "P908" "P2905" "P2986" "P1068" "P2946"
## [46] "P2904" "P1878" "P2883" "P2973" "P3533" "P3019" "P2865" "P2864" "P1056"
## [55] "P1152" "P2937" "P2876" "P3007" "P2978" "P2950" "P2871" "P2953" "P2917"
## [64] "P2948" "P609"
if (length(unique(pdat[["Serie"]])) >= 2) {
aov = anova_test(wdat, score.tde.pos ~ score.tde.pre + grupo*Serie)
laov[["grupo:Serie"]] <- merge(get_anova_table(aov), laov[["grupo:Serie"]],
by="Effect", suffixes = c("","'"))
df = get_anova_table(aov)
}
| Effect | DFn | DFd | F | p | p<.05 | ges |
|---|---|---|---|---|---|---|
| score.tde.pre | 1 | 1047 | 3720.788 | 0.000 | * | 0.780 |
| grupo | 1 | 1047 | 23.855 | 0.000 | * | 0.022 |
| Serie | 3 | 1047 | 34.727 | 0.000 | * | 0.090 |
| grupo:Serie | 3 | 1047 | 3.528 | 0.015 | * | 0.010 |
if (length(unique(pdat[["Serie"]])) >= 2) {
pwcs <- list()
pwcs[["Serie"]] <- emmeans_test(
group_by(wdat, grupo), score.tde.pos ~ Serie,
covariate = score.tde.pre, p.adjust.method = "bonferroni")
pwcs[["grupo"]] <- emmeans_test(
group_by(wdat, Serie), score.tde.pos ~ grupo,
covariate = score.tde.pre, p.adjust.method = "bonferroni")
pwc <- plyr::rbind.fill(pwcs[["grupo"]], pwcs[["Serie"]])
pwc <- pwc[,c("grupo","Serie", colnames(pwc)[!colnames(pwc) %in% c("grupo","Serie")])]
}
| grupo | Serie | term | .y. | group1 | group2 | df | statistic | p | p.adj | p.adj.signif |
|---|---|---|---|---|---|---|---|---|---|---|
| 6 ano | score.tde.pre*grupo | score.tde.pos | Controle | Experimental | 1047 | -0.249 | 0.803 | 0.803 | ns | |
| 7 ano | score.tde.pre*grupo | score.tde.pos | Controle | Experimental | 1047 | -4.500 | 0.000 | 0.000 | **** | |
| 8 ano | score.tde.pre*grupo | score.tde.pos | Controle | Experimental | 1047 | -3.348 | 0.001 | 0.001 | *** | |
| 9 ano | score.tde.pre*grupo | score.tde.pos | Controle | Experimental | 1047 | -1.694 | 0.091 | 0.091 | ns | |
| Controle | score.tde.pre*Serie | score.tde.pos | 6 ano | 7 ano | 1047 | 1.644 | 0.100 | 0.602 | ns | |
| Controle | score.tde.pre*Serie | score.tde.pos | 6 ano | 8 ano | 1047 | -2.433 | 0.015 | 0.091 | ns | |
| Controle | score.tde.pre*Serie | score.tde.pos | 6 ano | 9 ano | 1047 | -5.074 | 0.000 | 0.000 | **** | |
| Controle | score.tde.pre*Serie | score.tde.pos | 7 ano | 8 ano | 1047 | -3.939 | 0.000 | 0.001 | *** | |
| Controle | score.tde.pre*Serie | score.tde.pos | 7 ano | 9 ano | 1047 | -6.756 | 0.000 | 0.000 | **** | |
| Controle | score.tde.pre*Serie | score.tde.pos | 8 ano | 9 ano | 1047 | -2.300 | 0.022 | 0.130 | ns | |
| Experimental | score.tde.pre*Serie | score.tde.pos | 6 ano | 7 ano | 1047 | -2.574 | 0.010 | 0.061 | ns | |
| Experimental | score.tde.pre*Serie | score.tde.pos | 6 ano | 8 ano | 1047 | -6.514 | 0.000 | 0.000 | **** | |
| Experimental | score.tde.pre*Serie | score.tde.pos | 6 ano | 9 ano | 1047 | -7.114 | 0.000 | 0.000 | **** | |
| Experimental | score.tde.pre*Serie | score.tde.pos | 7 ano | 8 ano | 1047 | -4.242 | 0.000 | 0.000 | *** | |
| Experimental | score.tde.pre*Serie | score.tde.pos | 7 ano | 9 ano | 1047 | -4.930 | 0.000 | 0.000 | **** | |
| Experimental | score.tde.pre*Serie | score.tde.pos | 8 ano | 9 ano | 1047 | -0.688 | 0.492 | 1.000 | ns |
if (length(unique(pdat[["Serie"]])) >= 2) {
pwc.long <- emmeans_test(dplyr::group_by_at(wdat.long, c("grupo","Serie")),
score.tde ~ time,
p.adjust.method = "bonferroni")
lpwc[["grupo:Serie"]] <- merge(plyr::rbind.fill(pwc, pwc.long),
lpwc[["grupo:Serie"]],
by=c("grupo","Serie","term",".y.","group1","group2"),
suffixes = c("","'"))
}
| grupo | Serie | term | .y. | group1 | group2 | df | statistic | p | p.adj | p.adj.signif |
|---|---|---|---|---|---|---|---|---|---|---|
| Controle | 6 ano | time | score.tde | pre | pos | 2096 | 1.733 | 0.083 | 0.083 | ns |
| Controle | 7 ano | time | score.tde | pre | pos | 2096 | 2.740 | 0.006 | 0.006 | ** |
| Controle | 8 ano | time | score.tde | pre | pos | 2096 | 0.783 | 0.433 | 0.433 | ns |
| Controle | 9 ano | time | score.tde | pre | pos | 2096 | -0.131 | 0.896 | 0.896 | ns |
| Experimental | 6 ano | time | score.tde | pre | pos | 2096 | 1.773 | 0.076 | 0.076 | ns |
| Experimental | 7 ano | time | score.tde | pre | pos | 2096 | 0.944 | 0.345 | 0.345 | ns |
| Experimental | 8 ano | time | score.tde | pre | pos | 2096 | -0.962 | 0.336 | 0.336 | ns |
| Experimental | 9 ano | time | score.tde | pre | pos | 2096 | -1.132 | 0.258 | 0.258 | ns |
if (length(unique(pdat[["Serie"]])) >= 2) {
ds <- get.descriptives(wdat, "score.tde.pos", c("grupo","Serie"), covar = "score.tde.pre")
ds <- merge(ds[ds$variable != "score.tde.pre",],
ds[ds$variable == "score.tde.pre", !colnames(ds) %in% c("variable")],
by = c("grupo","Serie"), all.x = T, suffixes = c("", ".score.tde.pre"))
ds <- merge(get_emmeans(pwcs[["grupo"]]), ds,
by = c("grupo","Serie"), suffixes = c(".emms", ""))
ds <- ds[,c("grupo","Serie","n","mean.score.tde.pre","se.score.tde.pre",
"mean","se","emmean","se.emms","conf.low","conf.high")]
colnames(ds) <- c("grupo","Serie", "N", paste0(c("M","SE")," (pre)"),
paste0(c("M","SE"), " (unadj)"),
paste0(c("M", "SE"), " (adj)"), "conf.low", "conf.high")
lemms[["grupo:Serie"]] <- merge(ds, lemms[["grupo:Serie"]],
by=c("grupo","Serie"), suffixes = c("","'"))
}
| grupo | Serie | N | M (pre) | SE (pre) | M (unadj) | SE (unadj) | M (adj) | SE (adj) | conf.low | conf.high |
|---|---|---|---|---|---|---|---|---|---|---|
| Controle | 6 ano | 126 | 28.444 | 1.766 | 24.619 | 1.828 | 32.399 | 0.756 | 30.915 | 33.882 |
| Controle | 7 ano | 127 | 34.024 | 1.632 | 28.000 | 1.773 | 30.663 | 0.744 | 29.204 | 32.123 |
| Controle | 8 ano | 86 | 42.430 | 1.785 | 40.337 | 1.933 | 35.292 | 0.906 | 33.514 | 37.069 |
| Controle | 9 ano | 116 | 46.612 | 1.611 | 46.914 | 1.537 | 38.034 | 0.790 | 36.483 | 39.584 |
| Experimental | 6 ano | 150 | 28.607 | 1.324 | 25.020 | 1.367 | 32.651 | 0.694 | 31.288 | 34.013 |
| Experimental | 7 ano | 170 | 36.294 | 1.168 | 34.500 | 1.284 | 35.081 | 0.642 | 33.822 | 36.340 |
| Experimental | 8 ano | 141 | 39.248 | 1.525 | 41.255 | 1.600 | 39.128 | 0.705 | 37.744 | 40.512 |
| Experimental | 9 ano | 140 | 43.143 | 1.354 | 45.514 | 1.288 | 39.815 | 0.713 | 38.416 | 41.215 |
if (length(unique(pdat[["Serie"]])) >= 2) {
ggPlotAoC2(pwcs, "grupo", "Serie", aov, ylab = "Writing (TDE)",
subtitle = which(aov$Effect == "grupo:Serie"), addParam = "errorbar") +
ggplot2::scale_color_manual(values = color[["Serie"]]) +
ggplot2::ylab("Writing (TDE)") +
theme(axis.title = element_text(size = 14),
legend.text = element_text(size = 16),
plot.subtitle = element_text(size = 18)) +
if (ymin.ci < ymax.ci) ggplot2::ylim(ymin.ci, ymax.ci)
}
## Scale for colour is already present.
## Adding another scale for colour, which will replace the existing scale.
if (length(unique(pdat[["Serie"]])) >= 2) {
ggPlotAoC2(pwcs, "Serie", "grupo", aov, ylab = "Writing (TDE)",
subtitle = which(aov$Effect == "grupo:Serie"), addParam = "errorbar") +
ggplot2::scale_color_manual(values = color[["grupo"]]) +
ggplot2::ylab("Writing (TDE)") +
theme(axis.title = element_text(size = 14),
legend.text = element_text(size = 16),
plot.subtitle = element_text(size = 18)) +
if (ymin.ci < ymax.ci) ggplot2::ylim(ymin.ci, ymax.ci)
}
## Scale for colour is already present.
## Adding another scale for colour, which will replace the existing scale.
if (length(unique(pdat[["Serie"]])) >= 2) {
plots <- twoWayAncovaBoxPlots(
wdat, "score.tde.pos", c("grupo","Serie"), aov, pwcs, covar = "score.tde.pre",
theme = "classic", color = color[["grupo:Serie"]],
subtitle = which(aov$Effect == "grupo:Serie"))
}
if (length(unique(pdat[["Serie"]])) >= 2) {
plots[["grupo:Serie"]] + ggplot2::ylab("Writing (TDE)") +
ggplot2::scale_x_discrete(labels=c('pre', 'pos')) +
if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}
if (length(unique(pdat[["Serie"]])) >= 2) {
plots <- twoWayAncovaBoxPlots(
wdat.long, "score.tde", c("grupo","Serie"), aov, pwc.long,
pre.post = "time",
theme = "classic", color = color$prepost)
}
if (length(unique(pdat[["Serie"]])) >= 2)
plots[["grupo:Serie"]] + ggplot2::ylab("Writing (TDE)") +
if (ymin < ymax) ggplot2::ylim(ymin, ymax)
if (length(unique(pdat[["Serie"]])) >= 2) {
ggscatter(wdat, x = "score.tde.pre", y = "score.tde.pos", size = 0.5,
facet.by = c("grupo","Serie"), add = "reg.line")+
stat_regline_equation(
aes(label = paste(..eq.label.., ..rr.label.., sep = "~~~~"))
) +
ggplot2::xlab("Writing (TDE)") +
ggplot2::ylab("Writing (TDE)") +
theme(axis.title = element_text(size = 14),
legend.text = element_text(size = 16),
plot.subtitle = element_text(size = 18)) +
if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}
if (length(unique(pdat[["Serie"]])) >= 2) {
ggscatter(wdat, x = "score.tde.pre", y = "score.tde.pos", size = 0.5,
color = "grupo", facet.by = "Serie", add = "reg.line")+
stat_regline_equation(
aes(label = paste(..eq.label.., ..rr.label.., sep = "~~~~"), color = grupo)
) +
ggplot2::labs(subtitle = rstatix::get_test_label(aov, detailed = T, row = which(aov$Effect == "grupo:Serie"))) +
ggplot2::scale_color_manual(values = color[["grupo"]]) +
ggplot2::xlab("Writing (TDE)") +
ggplot2::ylab("Writing (TDE)") +
theme(axis.title = element_text(size = 14),
legend.text = element_text(size = 16),
plot.subtitle = element_text(size = 18)) +
if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}
if (length(unique(pdat[["Serie"]])) >= 2) {
ggscatter(wdat, x = "score.tde.pre", y = "score.tde.pos", size = 0.5,
color = "Serie", facet.by = "grupo", add = "reg.line")+
stat_regline_equation(
aes(label = paste(..eq.label.., ..rr.label.., sep = "~~~~"), color = Serie)
) +
ggplot2::labs(subtitle = rstatix::get_test_label(aov, detailed = T, row = which(aov$Effect == "grupo:Serie"))) +
ggplot2::scale_color_manual(values = color[["Serie"]]) +
ggplot2::xlab("Writing (TDE)") +
ggplot2::ylab("Writing (TDE)") +
theme(axis.title = element_text(size = 14),
legend.text = element_text(size = 16),
plot.subtitle = element_text(size = 18)) +
if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}
if (length(unique(pdat[["Serie"]])) >= 2)
res <- augment(lm(score.tde.pos ~ score.tde.pre + grupo*Serie, data = wdat))
if (length(unique(pdat[["Serie"]])) >= 2)
shapiro_test(res$.resid)
## # A tibble: 1 × 3
## variable statistic p.value
## <chr> <dbl> <dbl>
## 1 res$.resid 0.996 0.00727
if (length(unique(pdat[["Serie"]])) >= 2)
levene_test(res, .resid ~ grupo*Serie)
## # A tibble: 1 × 4
## df1 df2 statistic p
## <int> <int> <dbl> <dbl>
## 1 7 1048 7.87 0.00000000252
pdat = remove_group_data(dat[!is.na(dat[["grupo"]]) & !is.na(dat[["score.tde.quintile"]]),],
"score.tde.pos", c("grupo","score.tde.quintile"))
pdat = pdat[pdat[["score.tde.quintile"]] %in% do.call(
intersect, lapply(unique(pdat[["grupo"]]), FUN = function(x) {
unique(pdat[["score.tde.quintile"]][which(pdat[["grupo"]] == x)])
})),]
pdat[["grupo"]] = factor(pdat[["grupo"]], level[["grupo"]])
pdat[["score.tde.quintile"]] = factor(
pdat[["score.tde.quintile"]],
level[["score.tde.quintile"]][level[["score.tde.quintile"]] %in% unique(pdat[["score.tde.quintile"]])])
pdat.long <- rbind(pdat[,c("id","grupo","score.tde.quintile")], pdat[,c("id","grupo","score.tde.quintile")])
pdat.long[["time"]] <- c(rep("pre", nrow(pdat)), rep("pos", nrow(pdat)))
pdat.long[["time"]] <- factor(pdat.long[["time"]], c("pre","pos"))
pdat.long[["score.tde"]] <- c(pdat[["score.tde.pre"]], pdat[["score.tde.pos"]])
if (length(unique(pdat[["score.tde.quintile"]])) >= 2) {
aov = anova_test(pdat, score.tde.pos ~ score.tde.pre + grupo*score.tde.quintile)
laov[["grupo:score.tde.quintile"]] <- get_anova_table(aov)
}
if (length(unique(pdat[["score.tde.quintile"]])) >= 2) {
pwcs <- list()
pwcs[["score.tde.quintile"]] <- emmeans_test(
group_by(pdat, grupo), score.tde.pos ~ score.tde.quintile,
covariate = score.tde.pre, p.adjust.method = "bonferroni")
pwcs[["grupo"]] <- emmeans_test(
group_by(pdat, score.tde.quintile), score.tde.pos ~ grupo,
covariate = score.tde.pre, p.adjust.method = "bonferroni")
pwc <- plyr::rbind.fill(pwcs[["grupo"]], pwcs[["score.tde.quintile"]])
pwc <- pwc[,c("grupo","score.tde.quintile", colnames(pwc)[!colnames(pwc) %in% c("grupo","score.tde.quintile")])]
}
if (length(unique(pdat[["score.tde.quintile"]])) >= 2) {
pwc.long <- emmeans_test(dplyr::group_by_at(pdat.long, c("grupo","score.tde.quintile")),
score.tde ~ time,
p.adjust.method = "bonferroni")
lpwc[["grupo:score.tde.quintile"]] <- plyr::rbind.fill(pwc, pwc.long)
}
if (length(unique(pdat[["score.tde.quintile"]])) >= 2) {
ds <- get.descriptives(pdat, "score.tde.pos", c("grupo","score.tde.quintile"), covar = "score.tde.pre")
ds <- merge(ds[ds$variable != "score.tde.pre",],
ds[ds$variable == "score.tde.pre", !colnames(ds) %in% c("variable")],
by = c("grupo","score.tde.quintile"), all.x = T, suffixes = c("", ".score.tde.pre"))
ds <- merge(get_emmeans(pwcs[["grupo"]]), ds,
by = c("grupo","score.tde.quintile"), suffixes = c(".emms", ""))
ds <- ds[,c("grupo","score.tde.quintile","n","mean.score.tde.pre","se.score.tde.pre","mean","se",
"emmean","se.emms","conf.low","conf.high")]
colnames(ds) <- c("grupo","score.tde.quintile", "N", paste0(c("M","SE")," (pre)"),
paste0(c("M","SE"), " (unadj)"),
paste0(c("M", "SE"), " (adj)"), "conf.low", "conf.high")
lemms[["grupo:score.tde.quintile"]] <- ds
}
if (length(unique(pdat[["score.tde.quintile"]])) >= 2) {
wdat = pdat
res = residuals(lm(score.tde.pos ~ score.tde.pre + grupo*score.tde.quintile, data = wdat))
non.normal = getNonNormal(res, wdat$id, plimit = 0.05)
wdat = wdat[!wdat$id %in% non.normal,]
wdat.long <- rbind(wdat[,c("id","grupo","score.tde.quintile")], wdat[,c("id","grupo","score.tde.quintile")])
wdat.long[["time"]] <- c(rep("pre", nrow(wdat)), rep("pos", nrow(wdat)))
wdat.long[["time"]] <- factor(wdat.long[["time"]], c("pre","pos"))
wdat.long[["score.tde"]] <- c(wdat[["score.tde.pre"]], wdat[["score.tde.pos"]])
ldat[["grupo:score.tde.quintile"]] = wdat
(non.normal)
}
## [1] "P984" "P1128" "P962" "P1129" "P3637" "P1971" "P1117" "P1126" "P2950"
## [10] "P2883" "P2910" "P3019" "P2982" "P2904" "P2864" "P2959" "P3054" "P1139"
## [19] "P2835" "P921" "P2983" "P2994" "P2880" "P2917" "P2848" "P2866" "P3005"
## [28] "P929" "P2870" "P572" "P3674" "P3548" "P3021" "P809" "P3080" "P2997"
## [37] "P3666" "P3660" "P2867" "P1878" "P2858" "P2846" "P1840" "P3007" "P3545"
## [46] "P3533" "P2861" "P2993" "P2953" "P1111" "P2969" "P1804" "P2876" "P1018"
## [55] "P3228" "P2854" "P2871" "P2929" "P908" "P2964" "P1046" "P2190" "P2879"
## [64] "P2948" "P1118" "P2967" "P2956" "P2973" "P2946" "P2865" "P2831" "P3000"
## [73] "P2995" "P976" "P2937" "P1145" "P3029" "P2971" "P2951" "P2886" "P2913"
## [82] "P2977" "P1885" "P3026" "P931" "P3475" "P924" "P2952" "P2974" "P1024"
## [91] "P3520" "P3136" "P914" "P3280" "P1130" "P1825" "P2850" "P2888" "P1968"
## [100] "P1083" "P1887" "P2905" "P3459" "P3574"
if (length(unique(pdat[["score.tde.quintile"]])) >= 2) {
aov = anova_test(wdat, score.tde.pos ~ score.tde.pre + grupo*score.tde.quintile)
laov[["grupo:score.tde.quintile"]] <- merge(get_anova_table(aov), laov[["grupo:score.tde.quintile"]],
by="Effect", suffixes = c("","'"))
df = get_anova_table(aov)
}
| Effect | DFn | DFd | F | p | p<.05 | ges |
|---|---|---|---|---|---|---|
| score.tde.pre | 1 | 1006 | 264.709 | 0.000 | * | 0.208 |
| grupo | 1 | 1006 | 37.367 | 0.000 | * | 0.036 |
| score.tde.quintile | 4 | 1006 | 3.315 | 0.010 | * | 0.013 |
| grupo:score.tde.quintile | 4 | 1006 | 2.738 | 0.028 | * | 0.011 |
if (length(unique(pdat[["score.tde.quintile"]])) >= 2) {
pwcs <- list()
pwcs[["score.tde.quintile"]] <- emmeans_test(
group_by(wdat, grupo), score.tde.pos ~ score.tde.quintile,
covariate = score.tde.pre, p.adjust.method = "bonferroni")
pwcs[["grupo"]] <- emmeans_test(
group_by(wdat, score.tde.quintile), score.tde.pos ~ grupo,
covariate = score.tde.pre, p.adjust.method = "bonferroni")
pwc <- plyr::rbind.fill(pwcs[["grupo"]], pwcs[["score.tde.quintile"]])
pwc <- pwc[,c("grupo","score.tde.quintile", colnames(pwc)[!colnames(pwc) %in% c("grupo","score.tde.quintile")])]
}
| grupo | score.tde.quintile | term | .y. | group1 | group2 | df | statistic | p | p.adj | p.adj.signif |
|---|---|---|---|---|---|---|---|---|---|---|
| 1st quintile | score.tde.pre*grupo | score.tde.pos | Controle | Experimental | 1006 | -2.176 | 0.030 | 0.030 | * | |
| 2nd quintile | score.tde.pre*grupo | score.tde.pos | Controle | Experimental | 1006 | -2.614 | 0.009 | 0.009 | ** | |
| 3rd quintile | score.tde.pre*grupo | score.tde.pos | Controle | Experimental | 1006 | -4.957 | 0.000 | 0.000 | **** | |
| 4th quintile | score.tde.pre*grupo | score.tde.pos | Controle | Experimental | 1006 | -3.161 | 0.002 | 0.002 | ** | |
| 5th quintile | score.tde.pre*grupo | score.tde.pos | Controle | Experimental | 1006 | -1.453 | 0.147 | 0.147 | ns | |
| Controle | score.tde.pre*score.tde.quintile | score.tde.pos | 1st quintile | 2nd quintile | 1006 | 1.565 | 0.118 | 1.000 | ns | |
| Controle | score.tde.pre*score.tde.quintile | score.tde.pos | 1st quintile | 3rd quintile | 1006 | 2.102 | 0.036 | 0.358 | ns | |
| Controle | score.tde.pre*score.tde.quintile | score.tde.pos | 1st quintile | 4th quintile | 1006 | -0.118 | 0.906 | 1.000 | ns | |
| Controle | score.tde.pre*score.tde.quintile | score.tde.pos | 1st quintile | 5th quintile | 1006 | -0.370 | 0.711 | 1.000 | ns | |
| Controle | score.tde.pre*score.tde.quintile | score.tde.pos | 2nd quintile | 3rd quintile | 1006 | 1.201 | 0.230 | 1.000 | ns | |
| Controle | score.tde.pre*score.tde.quintile | score.tde.pos | 2nd quintile | 4th quintile | 1006 | -1.486 | 0.138 | 1.000 | ns | |
| Controle | score.tde.pre*score.tde.quintile | score.tde.pos | 2nd quintile | 5th quintile | 1006 | -1.515 | 0.130 | 1.000 | ns | |
| Controle | score.tde.pre*score.tde.quintile | score.tde.pos | 3rd quintile | 4th quintile | 1006 | -3.359 | 0.001 | 0.008 | ** | |
| Controle | score.tde.pre*score.tde.quintile | score.tde.pos | 3rd quintile | 5th quintile | 1006 | -3.197 | 0.001 | 0.014 | * | |
| Controle | score.tde.pre*score.tde.quintile | score.tde.pos | 4th quintile | 5th quintile | 1006 | -0.703 | 0.482 | 1.000 | ns | |
| Experimental | score.tde.pre*score.tde.quintile | score.tde.pos | 1st quintile | 2nd quintile | 1006 | 0.882 | 0.378 | 1.000 | ns | |
| Experimental | score.tde.pre*score.tde.quintile | score.tde.pos | 1st quintile | 3rd quintile | 1006 | -0.005 | 0.996 | 1.000 | ns | |
| Experimental | score.tde.pre*score.tde.quintile | score.tde.pos | 1st quintile | 4th quintile | 1006 | -0.482 | 0.630 | 1.000 | ns | |
| Experimental | score.tde.pre*score.tde.quintile | score.tde.pos | 1st quintile | 5th quintile | 1006 | -0.099 | 0.921 | 1.000 | ns | |
| Experimental | score.tde.pre*score.tde.quintile | score.tde.pos | 2nd quintile | 3rd quintile | 1006 | -1.014 | 0.311 | 1.000 | ns | |
| Experimental | score.tde.pre*score.tde.quintile | score.tde.pos | 2nd quintile | 4th quintile | 1006 | -1.503 | 0.133 | 1.000 | ns | |
| Experimental | score.tde.pre*score.tde.quintile | score.tde.pos | 2nd quintile | 5th quintile | 1006 | -0.722 | 0.470 | 1.000 | ns | |
| Experimental | score.tde.pre*score.tde.quintile | score.tde.pos | 3rd quintile | 4th quintile | 1006 | -0.991 | 0.322 | 1.000 | ns | |
| Experimental | score.tde.pre*score.tde.quintile | score.tde.pos | 3rd quintile | 5th quintile | 1006 | -0.183 | 0.855 | 1.000 | ns | |
| Experimental | score.tde.pre*score.tde.quintile | score.tde.pos | 4th quintile | 5th quintile | 1006 | 0.707 | 0.480 | 1.000 | ns |
if (length(unique(pdat[["score.tde.quintile"]])) >= 2) {
pwc.long <- emmeans_test(dplyr::group_by_at(wdat.long, c("grupo","score.tde.quintile")),
score.tde ~ time,
p.adjust.method = "bonferroni")
lpwc[["grupo:score.tde.quintile"]] <- merge(plyr::rbind.fill(pwc, pwc.long),
lpwc[["grupo:score.tde.quintile"]],
by=c("grupo","score.tde.quintile","term",".y.","group1","group2"),
suffixes = c("","'"))
}
| grupo | score.tde.quintile | term | .y. | group1 | group2 | df | statistic | p | p.adj | p.adj.signif |
|---|---|---|---|---|---|---|---|---|---|---|
| Controle | 1st quintile | time | score.tde | pre | pos | 2014 | 1.024 | 0.306 | 0.306 | ns |
| Controle | 2nd quintile | time | score.tde | pre | pos | 2014 | 3.105 | 0.002 | 0.002 | ** |
| Controle | 3rd quintile | time | score.tde | pre | pos | 2014 | 4.794 | 0.000 | 0.000 | **** |
| Controle | 4th quintile | time | score.tde | pre | pos | 2014 | 3.089 | 0.002 | 0.002 | ** |
| Controle | 5th quintile | time | score.tde | pre | pos | 2014 | 2.704 | 0.007 | 0.007 | ** |
| Experimental | 1st quintile | time | score.tde | pre | pos | 2014 | -1.416 | 0.157 | 0.157 | ns |
| Experimental | 2nd quintile | time | score.tde | pre | pos | 2014 | 0.824 | 0.410 | 0.410 | ns |
| Experimental | 3rd quintile | time | score.tde | pre | pos | 2014 | 0.152 | 0.879 | 0.879 | ns |
| Experimental | 4th quintile | time | score.tde | pre | pos | 2014 | -0.569 | 0.569 | 0.569 | ns |
| Experimental | 5th quintile | time | score.tde | pre | pos | 2014 | 1.120 | 0.263 | 0.263 | ns |
if (length(unique(pdat[["score.tde.quintile"]])) >= 2) {
ds <- get.descriptives(wdat, "score.tde.pos", c("grupo","score.tde.quintile"), covar = "score.tde.pre")
ds <- merge(ds[ds$variable != "score.tde.pre",],
ds[ds$variable == "score.tde.pre", !colnames(ds) %in% c("variable")],
by = c("grupo","score.tde.quintile"), all.x = T, suffixes = c("", ".score.tde.pre"))
ds <- merge(get_emmeans(pwcs[["grupo"]]), ds,
by = c("grupo","score.tde.quintile"), suffixes = c(".emms", ""))
ds <- ds[,c("grupo","score.tde.quintile","n","mean.score.tde.pre","se.score.tde.pre",
"mean","se","emmean","se.emms","conf.low","conf.high")]
colnames(ds) <- c("grupo","score.tde.quintile", "N", paste0(c("M","SE")," (pre)"),
paste0(c("M","SE"), " (unadj)"),
paste0(c("M", "SE"), " (adj)"), "conf.low", "conf.high")
lemms[["grupo:score.tde.quintile"]] <- merge(ds, lemms[["grupo:score.tde.quintile"]],
by=c("grupo","score.tde.quintile"), suffixes = c("","'"))
}
| grupo | score.tde.quintile | N | M (pre) | SE (pre) | M (unadj) | SE (unadj) | M (adj) | SE (adj) | conf.low | conf.high |
|---|---|---|---|---|---|---|---|---|---|---|
| Controle | 1st quintile | 112 | 9.152 | 0.522 | 8.205 | 0.750 | 34.585 | 1.783 | 31.086 | 38.083 |
| Controle | 2nd quintile | 51 | 24.392 | 0.530 | 20.137 | 1.288 | 32.089 | 1.322 | 29.495 | 34.682 |
| Controle | 3rd quintile | 42 | 38.905 | 0.489 | 31.667 | 1.800 | 29.879 | 1.216 | 27.493 | 32.265 |
| Controle | 4th quintile | 125 | 47.544 | 0.223 | 44.840 | 0.850 | 34.874 | 0.932 | 33.046 | 36.702 |
| Controle | 5th quintile | 116 | 58.819 | 0.505 | 56.362 | 0.792 | 35.722 | 1.463 | 32.851 | 38.593 |
| Experimental | 1st quintile | 108 | 9.602 | 0.522 | 10.935 | 0.788 | 36.889 | 1.765 | 33.425 | 40.352 |
| Experimental | 2nd quintile | 101 | 25.842 | 0.347 | 25.040 | 0.976 | 35.619 | 1.016 | 33.625 | 37.613 |
| Experimental | 3rd quintile | 116 | 37.371 | 0.301 | 37.233 | 0.859 | 36.898 | 0.729 | 35.467 | 38.328 |
| Experimental | 4th quintile | 120 | 46.800 | 0.230 | 47.308 | 0.725 | 38.047 | 0.915 | 36.251 | 39.842 |
| Experimental | 5th quintile | 126 | 58.563 | 0.448 | 57.587 | 0.700 | 37.189 | 1.435 | 34.372 | 40.006 |
if (length(unique(pdat[["score.tde.quintile"]])) >= 2) {
ggPlotAoC2(pwcs, "grupo", "score.tde.quintile", aov, ylab = "Writing (TDE)",
subtitle = which(aov$Effect == "grupo:score.tde.quintile"), addParam = "errorbar") +
ggplot2::scale_color_manual(values = color[["score.tde.quintile"]]) +
ggplot2::ylab("Writing (TDE)") +
theme(axis.title = element_text(size = 14),
legend.text = element_text(size = 16),
plot.subtitle = element_text(size = 18)) +
if (ymin.ci < ymax.ci) ggplot2::ylim(ymin.ci, ymax.ci)
}
## Scale for colour is already present.
## Adding another scale for colour, which will replace the existing scale.
if (length(unique(pdat[["score.tde.quintile"]])) >= 2) {
ggPlotAoC2(pwcs, "score.tde.quintile", "grupo", aov, ylab = "Writing (TDE)",
subtitle = which(aov$Effect == "grupo:score.tde.quintile"), addParam = "errorbar") +
ggplot2::scale_color_manual(values = color[["grupo"]]) +
ggplot2::ylab("Writing (TDE)") +
theme(axis.title = element_text(size = 14),
legend.text = element_text(size = 16),
plot.subtitle = element_text(size = 18)) +
if (ymin.ci < ymax.ci) ggplot2::ylim(ymin.ci, ymax.ci)
}
## Scale for colour is already present.
## Adding another scale for colour, which will replace the existing scale.
if (length(unique(pdat[["score.tde.quintile"]])) >= 2) {
plots <- twoWayAncovaBoxPlots(
wdat, "score.tde.pos", c("grupo","score.tde.quintile"), aov, pwcs, covar = "score.tde.pre",
theme = "classic", color = color[["grupo:score.tde.quintile"]],
subtitle = which(aov$Effect == "grupo:score.tde.quintile"))
}
if (length(unique(pdat[["score.tde.quintile"]])) >= 2) {
plots[["grupo:score.tde.quintile"]] + ggplot2::ylab("Writing (TDE)") +
ggplot2::scale_x_discrete(labels=c('pre', 'pos')) +
if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}
## Warning: No shared levels found between `names(values)` of the manual scale and the
## data's colour values.
if (length(unique(pdat[["score.tde.quintile"]])) >= 2) {
plots <- twoWayAncovaBoxPlots(
wdat.long, "score.tde", c("grupo","score.tde.quintile"), aov, pwc.long,
pre.post = "time",
theme = "classic", color = color$prepost)
}
if (length(unique(pdat[["score.tde.quintile"]])) >= 2)
plots[["grupo:score.tde.quintile"]] + ggplot2::ylab("Writing (TDE)") +
if (ymin < ymax) ggplot2::ylim(ymin, ymax)
if (length(unique(pdat[["score.tde.quintile"]])) >= 2) {
ggscatter(wdat, x = "score.tde.pre", y = "score.tde.pos", size = 0.5,
facet.by = c("grupo","score.tde.quintile"), add = "reg.line")+
stat_regline_equation(
aes(label = paste(..eq.label.., ..rr.label.., sep = "~~~~"))
) +
ggplot2::xlab("Writing (TDE)") +
ggplot2::ylab("Writing (TDE)") +
theme(axis.title = element_text(size = 14),
legend.text = element_text(size = 16),
plot.subtitle = element_text(size = 18)) +
if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}
if (length(unique(pdat[["score.tde.quintile"]])) >= 2) {
ggscatter(wdat, x = "score.tde.pre", y = "score.tde.pos", size = 0.5,
color = "grupo", facet.by = "score.tde.quintile", add = "reg.line")+
stat_regline_equation(
aes(label = paste(..eq.label.., ..rr.label.., sep = "~~~~"), color = grupo)
) +
ggplot2::labs(subtitle = rstatix::get_test_label(aov, detailed = T, row = which(aov$Effect == "grupo:score.tde.quintile"))) +
ggplot2::scale_color_manual(values = color[["grupo"]]) +
ggplot2::xlab("Writing (TDE)") +
ggplot2::ylab("Writing (TDE)") +
theme(axis.title = element_text(size = 14),
legend.text = element_text(size = 16),
plot.subtitle = element_text(size = 18)) +
if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}
if (length(unique(pdat[["score.tde.quintile"]])) >= 2) {
ggscatter(wdat, x = "score.tde.pre", y = "score.tde.pos", size = 0.5,
color = "score.tde.quintile", facet.by = "grupo", add = "reg.line")+
stat_regline_equation(
aes(label = paste(..eq.label.., ..rr.label.., sep = "~~~~"), color = score.tde.quintile)
) +
ggplot2::labs(subtitle = rstatix::get_test_label(aov, detailed = T, row = which(aov$Effect == "grupo:score.tde.quintile"))) +
ggplot2::scale_color_manual(values = color[["score.tde.quintile"]]) +
ggplot2::xlab("Writing (TDE)") +
ggplot2::ylab("Writing (TDE)") +
theme(axis.title = element_text(size = 14),
legend.text = element_text(size = 16),
plot.subtitle = element_text(size = 18)) +
if (ymin < ymax) ggplot2::ylim(ymin, ymax)
}
if (length(unique(pdat[["score.tde.quintile"]])) >= 2)
res <- augment(lm(score.tde.pos ~ score.tde.pre + grupo*score.tde.quintile, data = wdat))
if (length(unique(pdat[["score.tde.quintile"]])) >= 2)
shapiro_test(res$.resid)
## # A tibble: 1 × 3
## variable statistic p.value
## <chr> <dbl> <dbl>
## 1 res$.resid 0.996 0.0129
if (length(unique(pdat[["score.tde.quintile"]])) >= 2)
levene_test(res, .resid ~ grupo*score.tde.quintile)
## # A tibble: 1 × 4
## df1 df2 statistic p
## <int> <int> <dbl> <dbl>
## 1 9 1007 5.39 0.000000314
df <- get.descriptives(ldat[["grupo"]], c(dv.pre, dv.pos), c("grupo"),
include.global = T, symmetry.test = T, normality.test = F)
df <- plyr::rbind.fill(
df, do.call(plyr::rbind.fill, lapply(lfatores2, FUN = function(f) {
if (nrow(dat) > 0 && sum(!is.na(unique(dat[[f]]))) > 1 && paste0("grupo:",f) %in% names(ldat))
get.descriptives(ldat[[paste0("grupo:",f)]], c(dv.pre,dv.pos), c("grupo", f),
symmetry.test = T, normality.test = F)
}))
)
df <- df[,c(fatores1[fatores1 %in% colnames(df)],"variable",
colnames(df)[!colnames(df) %in% c(fatores1,"variable")])]
| grupo | Sexo | Zona | Cor.Raca | Serie | score.tde.quintile | variable | n | mean | median | min | max | sd | se | ci | iqr | symmetry | skewness | kurtosis |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Controle | score.tde.pre | 424 | 37.351 | 45.0 | 0 | 75 | 20.069 | 0.975 | 1.916 | 34.00 | YES | -0.404 | -1.165 | |||||
| Experimental | score.tde.pre | 557 | 36.770 | 39.0 | 0 | 73 | 17.478 | 0.741 | 1.455 | 26.00 | YES | -0.313 | -0.796 | |||||
| score.tde.pre | 981 | 37.021 | 42.0 | 0 | 75 | 18.635 | 0.595 | 1.168 | 29.00 | YES | -0.358 | -0.971 | ||||||
| Controle | score.tde.pos | 424 | 35.432 | 40.0 | 0 | 73 | 20.965 | 1.018 | 2.001 | 38.00 | YES | -0.277 | -1.217 | |||||
| Experimental | score.tde.pos | 557 | 37.230 | 40.0 | 0 | 74 | 18.335 | 0.777 | 1.526 | 27.00 | YES | -0.294 | -0.858 | |||||
| score.tde.pos | 981 | 36.453 | 40.0 | 0 | 74 | 19.525 | 0.623 | 1.223 | 31.00 | YES | -0.305 | -1.008 | ||||||
| Controle | F | score.tde.pre | 208 | 40.635 | 47.0 | 0 | 72 | 18.428 | 1.278 | 2.519 | 28.00 | NO | -0.660 | -0.764 | ||||
| Controle | M | score.tde.pre | 211 | 33.934 | 42.0 | 0 | 75 | 21.161 | 1.457 | 2.872 | 38.00 | YES | -0.126 | -1.375 | ||||
| Experimental | F | score.tde.pre | 276 | 39.623 | 43.5 | 0 | 73 | 17.500 | 1.053 | 2.074 | 26.00 | YES | -0.490 | -0.692 | ||||
| Experimental | M | score.tde.pre | 279 | 34.082 | 36.0 | 0 | 71 | 17.200 | 1.030 | 2.027 | 26.00 | YES | -0.174 | -0.823 | ||||
| Controle | F | score.tde.pos | 208 | 38.615 | 44.0 | 0 | 71 | 19.482 | 1.351 | 2.663 | 30.00 | NO | -0.532 | -0.975 | ||||
| Controle | M | score.tde.pos | 211 | 32.393 | 33.0 | 0 | 73 | 22.040 | 1.517 | 2.991 | 38.00 | YES | -0.018 | -1.332 | ||||
| Experimental | F | score.tde.pos | 276 | 40.272 | 45.0 | 0 | 73 | 18.658 | 1.123 | 2.211 | 28.25 | YES | -0.484 | -0.805 | ||||
| Experimental | M | score.tde.pos | 279 | 34.484 | 37.0 | 0 | 74 | 17.582 | 1.053 | 2.072 | 25.00 | YES | -0.205 | -0.757 | ||||
| Controle | Rural | score.tde.pre | 228 | 35.956 | 43.5 | 0 | 69 | 20.084 | 1.330 | 2.621 | 37.00 | YES | -0.398 | -1.296 | ||||
| Controle | Urbana | score.tde.pre | 101 | 39.743 | 45.0 | 1 | 75 | 18.324 | 1.823 | 3.617 | 28.00 | YES | -0.349 | -0.771 | ||||
| Experimental | Rural | score.tde.pre | 260 | 34.215 | 34.5 | 0 | 73 | 17.945 | 1.113 | 2.192 | 27.50 | YES | -0.096 | -0.905 | ||||
| Experimental | Urbana | score.tde.pre | 151 | 38.318 | 42.0 | 0 | 71 | 17.068 | 1.389 | 2.745 | 23.50 | NO | -0.526 | -0.563 | ||||
| Controle | Rural | score.tde.pos | 228 | 34.978 | 42.0 | 0 | 72 | 21.528 | 1.426 | 2.809 | 38.25 | YES | -0.286 | -1.280 | ||||
| Controle | Urbana | score.tde.pos | 101 | 31.099 | 30.0 | 0 | 73 | 20.538 | 2.044 | 4.054 | 36.00 | YES | 0.126 | -1.232 | ||||
| Experimental | Rural | score.tde.pos | 260 | 34.777 | 36.0 | 0 | 72 | 19.125 | 1.186 | 2.336 | 32.00 | YES | -0.055 | -1.056 | ||||
| Experimental | Urbana | score.tde.pos | 151 | 36.099 | 40.0 | 0 | 74 | 18.449 | 1.501 | 2.967 | 25.50 | YES | -0.391 | -0.821 | ||||
| Controle | Parda | score.tde.pre | 150 | 36.320 | 43.0 | 0 | 66 | 19.333 | 1.578 | 3.119 | 33.00 | NO | -0.563 | -1.085 | ||||
| Controle | Indígena | score.tde.pre | 11 | 42.000 | 46.0 | 4 | 65 | 17.297 | 5.215 | 11.621 | 9.50 | NO | -1.005 | -0.104 | ||||
| Controle | Branca | score.tde.pre | 45 | 41.378 | 46.0 | 2 | 67 | 17.619 | 2.626 | 5.293 | 15.00 | NO | -0.795 | -0.473 | ||||
| Experimental | Parda | score.tde.pre | 175 | 33.851 | 35.0 | 0 | 68 | 17.760 | 1.343 | 2.650 | 28.00 | YES | -0.110 | -0.955 | ||||
| Experimental | Indígena | score.tde.pre | 15 | 27.067 | 26.0 | 6 | 54 | 17.065 | 4.406 | 9.450 | 27.00 | YES | 0.126 | -1.422 | ||||
| Experimental | Branca | score.tde.pre | 58 | 34.517 | 35.5 | 0 | 73 | 20.186 | 2.651 | 5.308 | 34.50 | YES | -0.030 | -1.118 | ||||
| Controle | Parda | score.tde.pos | 150 | 33.887 | 39.5 | 0 | 68 | 20.756 | 1.695 | 3.349 | 39.50 | YES | -0.286 | -1.375 | ||||
| Controle | Indígena | score.tde.pos | 11 | 45.636 | 52.0 | 4 | 63 | 19.931 | 6.009 | 13.390 | 19.50 | NO | -0.968 | -0.645 | ||||
| Controle | Branca | score.tde.pos | 45 | 36.600 | 43.0 | 0 | 72 | 20.175 | 3.007 | 6.061 | 28.00 | YES | -0.398 | -0.997 | ||||
| Experimental | Parda | score.tde.pos | 175 | 33.514 | 32.0 | 0 | 71 | 19.317 | 1.460 | 2.882 | 31.00 | YES | 0.015 | -1.092 | ||||
| Experimental | Indígena | score.tde.pos | 15 | 30.333 | 26.0 | 1 | 57 | 17.715 | 4.574 | 9.810 | 30.50 | YES | 0.117 | -1.542 | ||||
| Experimental | Branca | score.tde.pos | 58 | 34.586 | 34.5 | 0 | 72 | 20.910 | 2.746 | 5.498 | 32.00 | YES | 0.002 | -1.163 | ||||
| Controle | 6 ano | score.tde.pre | 126 | 28.444 | 25.0 | 0 | 63 | 19.827 | 1.766 | 3.496 | 37.00 | YES | 0.114 | -1.549 | ||||
| Controle | 7 ano | score.tde.pre | 127 | 34.024 | 41.0 | 0 | 69 | 18.393 | 1.632 | 3.230 | 30.00 | YES | -0.192 | -1.277 | ||||
| Controle | 8 ano | score.tde.pre | 86 | 42.430 | 46.5 | 0 | 72 | 16.556 | 1.785 | 3.550 | 18.50 | NO | -0.821 | 0.143 | ||||
| Controle | 9 ano | score.tde.pre | 116 | 46.612 | 51.0 | 0 | 75 | 17.352 | 1.611 | 3.191 | 14.25 | NO | -1.081 | 0.454 | ||||
| Experimental | 6 ano | score.tde.pre | 150 | 28.607 | 29.0 | 0 | 65 | 16.217 | 1.324 | 2.617 | 24.75 | YES | 0.006 | -0.955 | ||||
| Experimental | 7 ano | score.tde.pre | 170 | 36.294 | 37.0 | 0 | 68 | 15.233 | 1.168 | 2.306 | 22.00 | YES | -0.132 | -0.765 | ||||
| Experimental | 8 ano | score.tde.pre | 141 | 39.248 | 44.0 | 0 | 73 | 18.114 | 1.525 | 3.016 | 26.00 | NO | -0.545 | -0.691 | ||||
| Experimental | 9 ano | score.tde.pre | 140 | 43.143 | 45.0 | 0 | 71 | 16.016 | 1.354 | 2.676 | 22.25 | NO | -0.646 | -0.066 | ||||
| Controle | 6 ano | score.tde.pos | 126 | 24.619 | 20.0 | 0 | 66 | 20.516 | 1.828 | 3.617 | 40.75 | YES | 0.335 | -1.356 | ||||
| Controle | 7 ano | score.tde.pos | 127 | 28.000 | 24.0 | 0 | 70 | 19.979 | 1.773 | 3.508 | 34.50 | YES | 0.321 | -1.224 | ||||
| Controle | 8 ano | score.tde.pos | 86 | 40.337 | 43.5 | 0 | 71 | 17.930 | 1.933 | 3.844 | 26.75 | NO | -0.595 | -0.451 | ||||
| Controle | 9 ano | score.tde.pos | 116 | 46.914 | 50.0 | 0 | 73 | 16.558 | 1.537 | 3.045 | 18.25 | NO | -0.869 | 0.170 | ||||
| Experimental | 6 ano | score.tde.pos | 150 | 25.020 | 23.0 | 0 | 65 | 16.738 | 1.367 | 2.701 | 27.00 | YES | 0.452 | -0.667 | ||||
| Experimental | 7 ano | score.tde.pos | 170 | 34.500 | 37.0 | 0 | 67 | 16.741 | 1.284 | 2.535 | 25.75 | YES | -0.209 | -0.863 | ||||
| Experimental | 8 ano | score.tde.pos | 141 | 41.255 | 45.0 | 0 | 73 | 18.995 | 1.600 | 3.163 | 26.00 | NO | -0.561 | -0.642 | ||||
| Experimental | 9 ano | score.tde.pos | 140 | 45.514 | 49.0 | 0 | 74 | 15.245 | 1.288 | 2.547 | 19.50 | NO | -0.761 | 0.330 | ||||
| Controle | 1st quintile | score.tde.pre | 112 | 9.152 | 10.0 | 0 | 18 | 5.522 | 0.522 | 1.034 | 8.50 | YES | -0.089 | -1.225 | ||||
| Controle | 2nd quintile | score.tde.pre | 51 | 24.392 | 25.0 | 19 | 31 | 3.785 | 0.530 | 1.064 | 6.50 | YES | -0.049 | -1.183 | ||||
| Controle | 3rd quintile | score.tde.pre | 42 | 38.905 | 40.0 | 32 | 42 | 3.169 | 0.489 | 0.987 | 5.75 | NO | -0.602 | -1.073 | ||||
| Controle | 4th quintile | score.tde.pre | 125 | 47.544 | 48.0 | 43 | 51 | 2.497 | 0.223 | 0.442 | 4.00 | YES | -0.303 | -0.977 | ||||
| Controle | 5th quintile | score.tde.pre | 116 | 58.819 | 58.0 | 52 | 75 | 5.437 | 0.505 | 1.000 | 8.00 | NO | 0.749 | -0.080 | ||||
| Experimental | 1st quintile | score.tde.pre | 108 | 9.602 | 10.0 | 0 | 18 | 5.426 | 0.522 | 1.035 | 10.00 | YES | -0.174 | -1.164 | ||||
| Experimental | 2nd quintile | score.tde.pre | 101 | 25.842 | 26.0 | 19 | 31 | 3.489 | 0.347 | 0.689 | 6.00 | YES | -0.241 | -1.059 | ||||
| Experimental | 3rd quintile | score.tde.pre | 116 | 37.371 | 38.0 | 32 | 42 | 3.245 | 0.301 | 0.597 | 6.00 | YES | -0.131 | -1.302 | ||||
| Experimental | 4th quintile | score.tde.pre | 120 | 46.800 | 47.0 | 43 | 51 | 2.523 | 0.230 | 0.456 | 4.00 | YES | 0.068 | -1.184 | ||||
| Experimental | 5th quintile | score.tde.pre | 126 | 58.563 | 58.0 | 52 | 73 | 5.033 | 0.448 | 0.887 | 8.00 | NO | 0.662 | -0.409 | ||||
| Controle | 1st quintile | score.tde.pos | 112 | 8.205 | 5.0 | 0 | 28 | 7.936 | 0.750 | 1.486 | 12.25 | NO | 0.705 | -0.691 | ||||
| Controle | 2nd quintile | score.tde.pos | 51 | 20.137 | 20.0 | 4 | 45 | 9.200 | 1.288 | 2.588 | 11.50 | YES | 0.436 | 0.070 | ||||
| Controle | 3rd quintile | score.tde.pos | 42 | 31.667 | 30.0 | 11 | 59 | 11.665 | 1.800 | 3.635 | 17.75 | YES | 0.319 | -0.776 | ||||
| Controle | 4th quintile | score.tde.pos | 125 | 44.840 | 46.0 | 18 | 63 | 9.506 | 0.850 | 1.683 | 14.00 | NO | -0.520 | -0.442 | ||||
| Controle | 5th quintile | score.tde.pos | 116 | 56.362 | 56.5 | 31 | 73 | 8.531 | 0.792 | 1.569 | 10.25 | YES | -0.360 | -0.038 | ||||
| Experimental | 1st quintile | score.tde.pos | 108 | 10.935 | 10.0 | 0 | 36 | 8.185 | 0.788 | 1.561 | 12.00 | NO | 0.643 | -0.292 | ||||
| Experimental | 2nd quintile | score.tde.pos | 101 | 25.040 | 25.0 | 4 | 47 | 9.804 | 0.976 | 1.935 | 14.00 | YES | -0.110 | -0.678 | ||||
| Experimental | 3rd quintile | score.tde.pos | 116 | 37.233 | 39.0 | 16 | 55 | 9.256 | 0.859 | 1.702 | 14.25 | YES | -0.215 | -0.813 | ||||
| Experimental | 4th quintile | score.tde.pos | 120 | 47.308 | 48.0 | 22 | 69 | 7.944 | 0.725 | 1.436 | 9.25 | YES | -0.124 | 0.510 | ||||
| Experimental | 5th quintile | score.tde.pos | 126 | 57.587 | 57.0 | 39 | 74 | 7.862 | 0.700 | 1.386 | 11.75 | YES | -0.167 | -0.553 |
df <- do.call(plyr::rbind.fill, laov)
df <- df[!duplicated(df$Effect),]
| Effect | DFn | DFd | F | p | p<.05 | ges | DFn’ | DFd’ | F’ | p’ | p<.05’ | ges’ | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | grupo | 1 | 978 | 24.670 | 0.000 | * | 0.025 | 1 | 1118 | 13.989 | 0.000 | * | 0.012 |
| 2 | score.tde.pre | 1 | 978 | 5874.442 | 0.000 | * | 0.857 | 1 | 1118 | 2814.834 | 0.000 | * | 0.716 |
| 4 | grupo:Sexo | 1 | 969 | 0.548 | 0.459 | 0.001 | 1 | 1116 | 0.305 | 0.581 | 0.000 | ||
| 6 | Sexo | 1 | 969 | 0.058 | 0.810 | 0.000 | 1 | 1116 | 0.148 | 0.700 | 0.000 | ||
| 8 | grupo:Zona | 1 | 735 | 14.155 | 0.000 | * | 0.019 | 1 | 798 | 9.749 | 0.002 | * | 0.012 |
| 10 | Zona | 1 | 735 | 54.679 | 0.000 | * | 0.069 | 1 | 798 | 35.734 | 0.000 | * | 0.043 |
| 11 | Cor.Raca | 2 | 447 | 3.357 | 0.036 | * | 0.015 | 2 | 482 | 3.984 | 0.019 | * | 0.016 |
| 13 | grupo:Cor.Raca | 2 | 447 | 1.174 | 0.310 | 0.005 | 2 | 482 | 1.222 | 0.296 | 0.005 | ||
| 16 | grupo:Serie | 3 | 1047 | 3.528 | 0.015 | * | 0.010 | 3 | 1112 | 2.801 | 0.039 | * | 0.008 |
| 18 | Serie | 3 | 1047 | 34.727 | 0.000 | * | 0.090 | 3 | 1112 | 30.848 | 0.000 | * | 0.077 |
| 20 | grupo:score.tde.quintile | 4 | 1006 | 2.738 | 0.028 | * | 0.011 | 4 | 1110 | 1.400 | 0.232 | 0.005 | |
| 22 | score.tde.quintile | 4 | 1006 | 3.315 | 0.010 | * | 0.013 | 4 | 1110 | 3.862 | 0.004 | * | 0.014 |
df <- do.call(plyr::rbind.fill, lpwc)
df <- df[,c(names(lfatores)[names(lfatores) %in% colnames(df)],
names(df)[!names(df) %in% c(names(lfatores),"term",".y.")])]
| grupo | Sexo | Zona | Cor.Raca | Serie | score.tde.quintile | group1 | group2 | df | statistic | p | p.adj | p.adj.signif | df’ | statistic’ | p’ | p.adj’ | p.adj.signif’ |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Controle | pre | pos | 1958 | 1.465 | 0.143 | 0.143 | ns | 2238 | 3.143 | 0.002 | 0.002 | ** | |||||
| Experimental | pre | pos | 1958 | -0.402 | 0.688 | 0.688 | ns | 2238 | 1.295 | 0.195 | 0.195 | ns | |||||
| Controle | Experimental | 978 | -4.967 | 0.000 | 0.000 | **** | 1118 | -3.740 | 0.000 | 0.000 | *** | ||||||
| Controle | F | pre | pos | 1940 | 1.089 | 0.276 | 0.276 | ns | 2234 | 2.427 | 0.015 | 0.015 | * | ||||
| Controle | M | pre | pos | 1940 | 0.837 | 0.403 | 0.403 | ns | 2234 | 2.061 | 0.039 | 0.039 | * | ||||
| Controle | F | M | 969 | -0.398 | 0.691 | 0.691 | ns | 1116 | -0.159 | 0.874 | 0.874 | ns | |||||
| Experimental | F | pre | pos | 1940 | -0.403 | 0.687 | 0.687 | ns | 2234 | 0.857 | 0.391 | 0.391 | ns | ||||
| Experimental | M | pre | pos | 1940 | -0.251 | 0.802 | 0.802 | ns | 2234 | 0.994 | 0.320 | 0.320 | ns | ||||
| Experimental | F | M | 969 | 0.663 | 0.507 | 0.507 | ns | 1116 | 0.652 | 0.514 | 0.514 | ns | |||||
| F | Controle | Experimental | 969 | -3.977 | 0.000 | 0.000 | **** | 1116 | -3.048 | 0.002 | 0.002 | ** | |||||
| M | Controle | Experimental | 969 | -2.953 | 0.003 | 0.003 | ** | 1116 | -2.236 | 0.026 | 0.026 | * | |||||
| Controle | Rural | Urbana | 735 | 7.675 | 0.000 | 0.000 | **** | 798 | 6.249 | 0.000 | 0.000 | **** | |||||
| Controle | Rural | pre | pos | 1472 | 0.543 | 0.588 | 0.588 | ns | 1598 | 1.120 | 0.263 | 0.263 | ns | ||||
| Controle | Urbana | pre | pos | 1472 | 3.191 | 0.001 | 0.001 | ** | 1598 | 3.728 | 0.000 | 0.000 | *** | ||||
| Experimental | Rural | Urbana | 735 | 3.188 | 0.001 | 0.001 | ** | 798 | 2.559 | 0.011 | 0.011 | * | |||||
| Experimental | Rural | pre | pos | 1472 | -0.333 | 0.739 | 0.739 | ns | 1598 | 0.603 | 0.547 | 0.547 | ns | ||||
| Experimental | Urbana | pre | pos | 1472 | 1.001 | 0.317 | 0.317 | ns | 1598 | 1.793 | 0.073 | 0.073 | ns | ||||
| Rural | Controle | Experimental | 735 | -2.009 | 0.045 | 0.045 | * | 798 | -0.977 | 0.329 | 0.329 | ns | |||||
| Urbana | Controle | Experimental | 735 | -6.023 | 0.000 | 0.000 | **** | 798 | -4.521 | 0.000 | 0.000 | **** | |||||
| Controle | Branca | pre | pos | 896 | 1.172 | 0.241 | 0.241 | ns | 966 | 1.861 | 0.063 | 0.063 | ns | ||||
| Controle | Indígena | pre | pos | 896 | -0.441 | 0.659 | 0.659 | ns | 966 | -0.443 | 0.658 | 0.658 | ns | ||||
| Controle | Indígena | Branca | 447 | 2.687 | 0.007 | 0.022 | * | 482 | 2.857 | 0.004 | 0.013 | * | |||||
| Controle | Parda | Branca | 447 | 1.334 | 0.183 | 0.549 | ns | 482 | 1.348 | 0.178 | 0.535 | ns | |||||
| Controle | Parda | Indígena | 447 | -2.163 | 0.031 | 0.093 | ns | 482 | -2.350 | 0.019 | 0.057 | ns | |||||
| Controle | Parda | pre | pos | 896 | 1.090 | 0.276 | 0.276 | ns | 966 | 2.002 | 0.046 | 0.046 | * | ||||
| Experimental | Branca | pre | pos | 896 | -0.019 | 0.985 | 0.985 | ns | 966 | 0.377 | 0.707 | 0.707 | ns | ||||
| Experimental | Indígena | pre | pos | 896 | -0.463 | 0.644 | 0.644 | ns | 966 | -0.465 | 0.642 | 0.642 | ns | ||||
| Experimental | Indígena | Branca | 447 | 1.060 | 0.290 | 0.870 | ns | 482 | 1.201 | 0.230 | 0.691 | ns | |||||
| Experimental | Parda | Branca | 447 | -0.308 | 0.759 | 1.000 | ns | 482 | -0.313 | 0.755 | 1.000 | ns | |||||
| Experimental | Parda | Indígena | 447 | -1.314 | 0.190 | 0.569 | ns | 482 | -1.461 | 0.145 | 0.434 | ns | |||||
| Experimental | Parda | pre | pos | 896 | 0.163 | 0.870 | 0.870 | ns | 966 | 0.915 | 0.360 | 0.360 | ns | ||||
| Branca | Controle | Experimental | 447 | -2.442 | 0.015 | 0.015 | * | 482 | -2.420 | 0.016 | 0.016 | * | |||||
| Indígena | Controle | Experimental | 447 | 0.274 | 0.784 | 0.784 | ns | 482 | 0.354 | 0.723 | 0.723 | ns | |||||
| Parda | Controle | Experimental | 447 | -1.911 | 0.057 | 0.057 | ns | 482 | -1.857 | 0.064 | 0.064 | ns | |||||
| Controle | 6 ano | pre | pos | 2096 | 1.733 | 0.083 | 0.083 | ns | 2226 | 2.226 | 0.026 | 0.026 | * | ||||
| Controle | 7 ano | pre | pos | 2096 | 2.740 | 0.006 | 0.006 | ** | 2226 | 3.047 | 0.002 | 0.002 | ** | ||||
| Controle | 8 ano | pre | pos | 2096 | 0.783 | 0.433 | 0.433 | ns | 2226 | 1.066 | 0.287 | 0.287 | ns | ||||
| Controle | 9 ano | pre | pos | 2096 | -0.131 | 0.896 | 0.896 | ns | 2226 | 0.246 | 0.806 | 0.806 | ns | ||||
| Controle | 6 ano | 7 ano | 1047 | 1.644 | 0.100 | 0.602 | ns | 1112 | 0.755 | 0.451 | 1.000 | ns | |||||
| Controle | 6 ano | 8 ano | 1047 | -2.433 | 0.015 | 0.091 | ns | 1112 | -2.513 | 0.012 | 0.073 | ns | |||||
| Controle | 6 ano | 9 ano | 1047 | -5.074 | 0.000 | 0.000 | **** | 1112 | -4.792 | 0.000 | 0.000 | **** | |||||
| Controle | 7 ano | 8 ano | 1047 | -3.939 | 0.000 | 0.001 | *** | 1112 | -3.235 | 0.001 | 0.008 | ** | |||||
| Controle | 7 ano | 9 ano | 1047 | -6.756 | 0.000 | 0.000 | **** | 1112 | -5.654 | 0.000 | 0.000 | **** | |||||
| Controle | 8 ano | 9 ano | 1047 | -2.300 | 0.022 | 0.130 | ns | 1112 | -1.937 | 0.053 | 0.318 | ns | |||||
| Experimental | 6 ano | pre | pos | 2096 | 1.773 | 0.076 | 0.076 | ns | 2226 | 2.498 | 0.013 | 0.013 | * | ||||
| Experimental | 7 ano | pre | pos | 2096 | 0.944 | 0.345 | 0.345 | ns | 2226 | 1.665 | 0.096 | 0.096 | ns | ||||
| Experimental | 8 ano | pre | pos | 2096 | -0.962 | 0.336 | 0.336 | ns | 2226 | -0.986 | 0.324 | 0.324 | ns | ||||
| Experimental | 9 ano | pre | pos | 2096 | -1.132 | 0.258 | 0.258 | ns | 2226 | -0.596 | 0.551 | 0.551 | ns | ||||
| Experimental | 6 ano | 7 ano | 1047 | -2.574 | 0.010 | 0.061 | ns | 1112 | -2.506 | 0.012 | 0.074 | ns | |||||
| Experimental | 6 ano | 8 ano | 1047 | -6.514 | 0.000 | 0.000 | **** | 1112 | -6.849 | 0.000 | 0.000 | **** | |||||
| Experimental | 6 ano | 9 ano | 1047 | -7.114 | 0.000 | 0.000 | **** | 1112 | -6.535 | 0.000 | 0.000 | **** | |||||
| Experimental | 7 ano | 8 ano | 1047 | -4.242 | 0.000 | 0.000 | *** | 1112 | -4.734 | 0.000 | 0.000 | **** | |||||
| Experimental | 7 ano | 9 ano | 1047 | -4.930 | 0.000 | 0.000 | **** | 1112 | -4.449 | 0.000 | 0.000 | **** | |||||
| Experimental | 8 ano | 9 ano | 1047 | -0.688 | 0.492 | 1.000 | ns | 1112 | 0.281 | 0.779 | 1.000 | ns | |||||
| 6 ano | Controle | Experimental | 1047 | -0.249 | 0.803 | 0.803 | ns | 1112 | 0.121 | 0.904 | 0.904 | ns | |||||
| 7 ano | Controle | Experimental | 1047 | -4.500 | 0.000 | 0.000 | **** | 1112 | -3.134 | 0.002 | 0.002 | ** | |||||
| 8 ano | Controle | Experimental | 1047 | -3.348 | 0.001 | 0.001 | *** | 1112 | -3.222 | 0.001 | 0.001 | ** | |||||
| 9 ano | Controle | Experimental | 1047 | -1.694 | 0.091 | 0.091 | ns | 1112 | -1.070 | 0.285 | 0.285 | ns | |||||
| Controle | 1st quintile | pre | pos | 2014 | 1.024 | 0.306 | 0.306 | ns | 2222 | 0.622 | 0.534 | 0.534 | ns | ||||
| Controle | 2nd quintile | pre | pos | 2014 | 3.105 | 0.002 | 0.002 | ** | 2222 | 2.906 | 0.004 | 0.004 | ** | ||||
| Controle | 3rd quintile | pre | pos | 2014 | 4.794 | 0.000 | 0.000 | **** | 2222 | 5.243 | 0.000 | 0.000 | **** | ||||
| Controle | 4th quintile | pre | pos | 2014 | 3.089 | 0.002 | 0.002 | ** | 2222 | 3.992 | 0.000 | 0.000 | **** | ||||
| Controle | 5th quintile | pre | pos | 2014 | 2.704 | 0.007 | 0.007 | ** | 2222 | 3.512 | 0.000 | 0.000 | *** | ||||
| Controle | 1st quintile | 2nd quintile | 1006 | 1.565 | 0.118 | 1.000 | ns | 1110 | 2.058 | 0.040 | 0.398 | ns | |||||
| Controle | 1st quintile | 3rd quintile | 1006 | 2.102 | 0.036 | 0.358 | ns | 1110 | 3.034 | 0.002 | 0.025 | * | |||||
| Controle | 1st quintile | 4th quintile | 1006 | -0.118 | 0.906 | 1.000 | ns | 1110 | 1.355 | 0.176 | 1.000 | ns | |||||
| Controle | 1st quintile | 5th quintile | 1006 | -0.370 | 0.711 | 1.000 | ns | 1110 | 1.061 | 0.289 | 1.000 | ns | |||||
| Controle | 2nd quintile | 3rd quintile | 1006 | 1.201 | 0.230 | 1.000 | ns | 1110 | 1.940 | 0.053 | 0.527 | ns | |||||
| Controle | 2nd quintile | 4th quintile | 1006 | -1.486 | 0.138 | 1.000 | ns | 1110 | 0.038 | 0.970 | 1.000 | ns | |||||
| Controle | 2nd quintile | 5th quintile | 1006 | -1.515 | 0.130 | 1.000 | ns | 1110 | 0.000 | 1.000 | 1.000 | ns | |||||
| Controle | 3rd quintile | 4th quintile | 1006 | -3.359 | 0.001 | 0.008 | ** | 1110 | -2.364 | 0.018 | 0.183 | ns | |||||
| Controle | 3rd quintile | 5th quintile | 1006 | -3.197 | 0.001 | 0.014 | * | 1110 | -1.923 | 0.055 | 0.548 | ns | |||||
| Controle | 4th quintile | 5th quintile | 1006 | -0.703 | 0.482 | 1.000 | ns | 1110 | -0.057 | 0.954 | 1.000 | ns | |||||
| Experimental | 1st quintile | pre | pos | 2014 | -1.416 | 0.157 | 0.157 | ns | 2222 | -1.406 | 0.160 | 0.160 | ns | ||||
| Experimental | 2nd quintile | pre | pos | 2014 | 0.824 | 0.410 | 0.410 | ns | 2222 | 1.055 | 0.292 | 0.292 | ns | ||||
| Experimental | 3rd quintile | pre | pos | 2014 | 0.152 | 0.879 | 0.879 | ns | 2222 | 2.465 | 0.014 | 0.014 | * | ||||
| Experimental | 4th quintile | pre | pos | 2014 | -0.569 | 0.569 | 0.569 | ns | 2222 | 1.583 | 0.114 | 0.114 | ns | ||||
| Experimental | 5th quintile | pre | pos | 2014 | 1.120 | 0.263 | 0.263 | ns | 2222 | 2.436 | 0.015 | 0.015 | * | ||||
| Experimental | 1st quintile | 2nd quintile | 1006 | 0.882 | 0.378 | 1.000 | ns | 1110 | 1.705 | 0.088 | 0.884 | ns | |||||
| Experimental | 1st quintile | 3rd quintile | 1006 | -0.005 | 0.996 | 1.000 | ns | 1110 | 1.916 | 0.056 | 0.556 | ns | |||||
| Experimental | 1st quintile | 4th quintile | 1006 | -0.482 | 0.630 | 1.000 | ns | 1110 | 1.324 | 0.186 | 1.000 | ns | |||||
| Experimental | 1st quintile | 5th quintile | 1006 | -0.099 | 0.921 | 1.000 | ns | 1110 | 1.342 | 0.180 | 1.000 | ns | |||||
| Experimental | 2nd quintile | 3rd quintile | 1006 | -1.014 | 0.311 | 1.000 | ns | 1110 | 1.008 | 0.314 | 1.000 | ns | |||||
| Experimental | 2nd quintile | 4th quintile | 1006 | -1.503 | 0.133 | 1.000 | ns | 1110 | 0.462 | 0.644 | 1.000 | ns | |||||
| Experimental | 2nd quintile | 5th quintile | 1006 | -0.722 | 0.470 | 1.000 | ns | 1110 | 0.750 | 0.453 | 1.000 | ns | |||||
| Experimental | 3rd quintile | 4th quintile | 1006 | -0.991 | 0.322 | 1.000 | ns | 1110 | -0.437 | 0.662 | 1.000 | ns | |||||
| Experimental | 3rd quintile | 5th quintile | 1006 | -0.183 | 0.855 | 1.000 | ns | 1110 | 0.248 | 0.804 | 1.000 | ns | |||||
| Experimental | 4th quintile | 5th quintile | 1006 | 0.707 | 0.480 | 1.000 | ns | 1110 | 0.730 | 0.466 | 1.000 | ns | |||||
| 1st quintile | Controle | Experimental | 1006 | -2.176 | 0.030 | 0.030 | * | 1110 | -1.642 | 0.101 | 0.101 | ns | |||||
| 2nd quintile | Controle | Experimental | 1006 | -2.614 | 0.009 | 0.009 | ** | 1110 | -2.002 | 0.046 | 0.046 | * | |||||
| 3rd quintile | Controle | Experimental | 1006 | -4.957 | 0.000 | 0.000 | **** | 1110 | -3.647 | 0.000 | 0.000 | *** | |||||
| 4th quintile | Controle | Experimental | 1006 | -3.161 | 0.002 | 0.002 | ** | 1110 | -1.944 | 0.052 | 0.052 | ns | |||||
| 5th quintile | Controle | Experimental | 1006 | -1.453 | 0.147 | 0.147 | ns | 1110 | -0.974 | 0.330 | 0.330 | ns |
df <- do.call(plyr::rbind.fill, lemms)
df[["N-N'"]] <- df[["N"]] - df[["N'"]]
df <- df[,c(names(lfatores)[names(lfatores) %in% colnames(df)],
names(df)[!names(df) %in% names(lfatores)])]
| grupo | Sexo | Zona | Cor.Raca | Serie | score.tde.quintile | N | M (pre) | SE (pre) | M (unadj) | SE (unadj) | M (adj) | SE (adj) | conf.low | conf.high | N’ | M (pre)’ | SE (pre)’ | M (unadj)’ | SE (unadj)’ | M (adj)’ | SE (adj)’ | conf.low’ | conf.high’ | N-N’ |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Controle | 424 | 37.351 | 0.975 | 35.432 | 1.018 | 35.112 | 0.358 | 34.409 | 35.815 | 485 | 37.631 | 0.871 | 33.816 | 0.953 | 33.348 | 0.480 | 32.405 | 34.290 | -61 | |||||
| Experimental | 557 | 36.770 | 0.741 | 37.230 | 0.777 | 37.473 | 0.313 | 36.860 | 38.087 | 636 | 36.748 | 0.670 | 35.376 | 0.749 | 35.733 | 0.419 | 34.910 | 36.556 | -79 | |||||
| Controle | F | 208 | 40.635 | 1.278 | 38.615 | 1.351 | 35.106 | 0.503 | 34.119 | 36.093 | 247 | 40.652 | 1.098 | 36.567 | 1.265 | 33.273 | 0.676 | 31.945 | 34.600 | -39 | ||||
| Controle | M | 211 | 33.934 | 1.457 | 32.393 | 1.517 | 35.389 | 0.499 | 34.410 | 36.368 | 238 | 34.496 | 1.332 | 30.962 | 1.410 | 33.427 | 0.688 | 32.077 | 34.776 | -27 | ||||
| Experimental | F | 276 | 39.623 | 1.053 | 40.272 | 1.123 | 37.744 | 0.436 | 36.889 | 38.600 | 319 | 39.408 | 0.941 | 38.138 | 1.086 | 36.008 | 0.594 | 34.842 | 37.173 | -43 | ||||
| Experimental | M | 279 | 34.082 | 1.030 | 34.484 | 1.053 | 37.335 | 0.434 | 36.483 | 38.187 | 317 | 34.073 | 0.931 | 32.596 | 1.011 | 35.457 | 0.597 | 34.285 | 36.628 | -38 | ||||
| Controle | Rural | 228 | 35.956 | 1.330 | 34.978 | 1.426 | 35.358 | 0.547 | 34.284 | 36.432 | 243 | 36.181 | 1.259 | 34.243 | 1.380 | 34.462 | 0.669 | 33.149 | 35.775 | -15 | ||||
| Controle | Urbana | 101 | 39.743 | 1.823 | 31.099 | 2.044 | 27.763 | 0.824 | 26.145 | 29.380 | 109 | 39.468 | 1.727 | 29.835 | 1.951 | 26.939 | 1.001 | 24.975 | 28.903 | -8 | ||||
| Experimental | Rural | 260 | 34.215 | 1.113 | 34.777 | 1.186 | 36.865 | 0.514 | 35.857 | 37.874 | 284 | 34.592 | 1.036 | 33.627 | 1.141 | 35.352 | 0.620 | 34.136 | 36.569 | -24 | ||||
| Experimental | Urbana | 151 | 38.318 | 1.389 | 36.099 | 1.501 | 34.161 | 0.673 | 32.840 | 35.483 | 167 | 37.850 | 1.287 | 34.108 | 1.462 | 32.745 | 0.807 | 31.160 | 34.330 | -16 | ||||
| Controle | Branca | 45 | 41.378 | 2.626 | 36.600 | 3.007 | 30.951 | 1.399 | 28.202 | 33.701 | 50 | 41.460 | 2.396 | 34.300 | 2.902 | 29.123 | 1.619 | 25.941 | 32.304 | -5 | ||||
| Controle | Indígena | 11 | 42.000 | 5.215 | 45.636 | 6.009 | 39.393 | 2.820 | 33.851 | 44.935 | 11 | 42.000 | 5.215 | 45.636 | 6.009 | 39.964 | 3.439 | 33.206 | 46.722 | 0 | ||||
| Controle | Parda | 150 | 36.320 | 1.578 | 33.887 | 1.695 | 33.075 | 0.763 | 31.576 | 34.574 | 162 | 36.741 | 1.485 | 32.463 | 1.634 | 31.613 | 0.895 | 29.854 | 33.373 | -12 | ||||
| Experimental | Branca | 58 | 34.517 | 2.651 | 34.586 | 2.746 | 35.499 | 1.226 | 33.088 | 37.909 | 61 | 34.623 | 2.526 | 33.311 | 2.713 | 34.404 | 1.459 | 31.537 | 37.270 | -3 | ||||
| Experimental | Indígena | 15 | 27.067 | 4.406 | 30.333 | 4.574 | 38.371 | 2.420 | 33.616 | 43.126 | 15 | 27.067 | 4.406 | 30.333 | 4.574 | 38.355 | 2.952 | 32.554 | 44.155 | 0 | ||||
| Experimental | Parda | 175 | 33.851 | 1.343 | 33.514 | 1.460 | 35.064 | 0.707 | 33.674 | 36.453 | 190 | 34.253 | 1.272 | 32.447 | 1.412 | 33.879 | 0.828 | 32.253 | 35.505 | -15 | ||||
| Controle | 6 ano | 126 | 28.444 | 1.766 | 24.619 | 1.828 | 32.399 | 0.756 | 30.915 | 33.882 | 134 | 28.993 | 1.687 | 24.231 | 1.741 | 31.423 | 0.889 | 29.678 | 33.168 | -8 | ||||
| Controle | 7 ano | 127 | 34.024 | 1.632 | 28.000 | 1.773 | 30.663 | 0.744 | 29.204 | 32.123 | 141 | 34.716 | 1.503 | 28.362 | 1.739 | 30.495 | 0.856 | 28.815 | 32.175 | -14 | ||||
| Controle | 8 ano | 86 | 42.430 | 1.785 | 40.337 | 1.933 | 35.292 | 0.906 | 33.514 | 37.069 | 89 | 42.584 | 1.737 | 39.787 | 1.897 | 34.967 | 1.081 | 32.846 | 37.087 | -3 | ||||
| Controle | 9 ano | 116 | 46.612 | 1.611 | 46.914 | 1.537 | 38.034 | 0.790 | 36.483 | 39.584 | 121 | 46.950 | 1.557 | 46.397 | 1.495 | 37.718 | 0.940 | 35.874 | 39.562 | -5 | ||||
| Experimental | 6 ano | 150 | 28.607 | 1.324 | 25.020 | 1.367 | 32.651 | 0.694 | 31.288 | 34.013 | 159 | 29.000 | 1.265 | 24.094 | 1.329 | 31.279 | 0.819 | 29.673 | 32.885 | -9 | ||||
| Experimental | 7 ano | 170 | 36.294 | 1.168 | 34.500 | 1.284 | 35.081 | 0.642 | 33.822 | 36.340 | 187 | 36.540 | 1.089 | 33.524 | 1.254 | 34.046 | 0.743 | 32.588 | 35.503 | -17 | ||||
| Experimental | 8 ano | 141 | 39.248 | 1.525 | 41.255 | 1.600 | 39.128 | 0.705 | 37.744 | 40.512 | 143 | 39.000 | 1.516 | 41.042 | 1.604 | 39.390 | 0.850 | 37.722 | 41.057 | -2 | ||||
| Experimental | 9 ano | 140 | 43.143 | 1.354 | 45.514 | 1.288 | 39.815 | 0.713 | 38.416 | 41.215 | 147 | 43.204 | 1.307 | 44.422 | 1.331 | 39.054 | 0.845 | 37.397 | 40.711 | -7 | ||||
| Controle | 1st quintile | 112 | 9.152 | 0.522 | 8.205 | 0.750 | 34.585 | 1.783 | 31.086 | 38.083 | 113 | 9.230 | 0.523 | 8.522 | 0.808 | 37.046 | 2.325 | 32.484 | 41.608 | -1 | ||||
| Controle | 2nd quintile | 51 | 24.392 | 0.530 | 20.137 | 1.288 | 32.089 | 1.322 | 29.495 | 34.682 | 59 | 24.542 | 0.492 | 19.966 | 1.686 | 32.835 | 1.666 | 29.566 | 36.104 | -8 | ||||
| Controle | 3rd quintile | 42 | 38.905 | 0.489 | 31.667 | 1.800 | 29.879 | 1.216 | 27.493 | 32.265 | 54 | 38.815 | 0.409 | 30.185 | 2.082 | 28.463 | 1.437 | 25.644 | 31.282 | -12 | ||||
| Controle | 4th quintile | 125 | 47.544 | 0.223 | 44.840 | 0.850 | 34.874 | 0.932 | 33.046 | 36.702 | 135 | 47.370 | 0.222 | 43.215 | 0.978 | 32.746 | 1.190 | 30.411 | 35.080 | -10 | ||||
| Controle | 5th quintile | 116 | 58.819 | 0.505 | 56.362 | 0.792 | 35.722 | 1.463 | 32.851 | 38.593 | 124 | 58.621 | 0.482 | 54.806 | 0.979 | 32.835 | 1.876 | 29.155 | 36.516 | -8 | ||||
| Experimental | 1st quintile | 108 | 9.602 | 0.522 | 10.935 | 0.788 | 36.889 | 1.765 | 33.425 | 40.352 | 112 | 9.777 | 0.515 | 11.384 | 0.898 | 39.349 | 2.290 | 34.856 | 43.842 | -4 | ||||
| Experimental | 2nd quintile | 101 | 25.842 | 0.347 | 25.040 | 0.976 | 35.619 | 1.016 | 33.625 | 37.613 | 117 | 25.855 | 0.316 | 24.675 | 1.128 | 36.203 | 1.292 | 33.668 | 38.737 | -16 | ||||
| Experimental | 3rd quintile | 116 | 37.371 | 0.301 | 37.233 | 0.859 | 36.898 | 0.729 | 35.467 | 38.328 | 141 | 37.383 | 0.268 | 34.872 | 1.096 | 34.614 | 0.886 | 32.876 | 36.352 | -25 | ||||
| Experimental | 4th quintile | 120 | 46.800 | 0.230 | 47.308 | 0.725 | 38.047 | 0.915 | 36.251 | 39.842 | 132 | 46.697 | 0.217 | 45.030 | 0.924 | 35.250 | 1.166 | 32.963 | 37.537 | -12 | ||||
| Experimental | 5th quintile | 126 | 58.563 | 0.448 | 57.587 | 0.700 | 37.189 | 1.435 | 34.372 | 40.006 | 134 | 58.336 | 0.434 | 55.791 | 0.917 | 34.111 | 1.839 | 30.503 | 37.720 | -8 |
df <- do.call(rbind, lapply(c("Sexo","Zona","Cor.Raca","Serie","Idade"), FUN = function(x) {
tdat2 <- tdat
tdat2[[x]][is.na(tdat2[[x]])] <- "Not declared"
count_(group_by(tdat2, grupo), x)
}))
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
| grupo | Sexo | n | Zona | Cor.Raca | Serie | Idade |
|---|---|---|---|---|---|---|
| Controle | F | 376 | ||||
| Controle | M | 393 | ||||
| Experimental | F | 508 | ||||
| Experimental | M | 528 | ||||
| Controle | 211 | Not declared | ||||
| Controle | 351 | Rural | ||||
| Controle | 207 | Urbana | ||||
| Experimental | 321 | Not declared | ||||
| Experimental | 426 | Rural | ||||
| Experimental | 289 | Urbana | ||||
| Controle | 77 | Branca | ||||
| Controle | 21 | Indígena | ||||
| Controle | 416 | Not declared | ||||
| Controle | 254 | Parda | ||||
| Controle | 1 | Preta | ||||
| Experimental | 3 | Amarela | ||||
| Experimental | 92 | Branca | ||||
| Experimental | 22 | Indígena | ||||
| Experimental | 619 | Not declared | ||||
| Experimental | 299 | Parda | ||||
| Experimental | 1 | Preta | ||||
| Controle | 215 | 6 ano | ||||
| Controle | 214 | 7 ano | ||||
| Controle | 163 | 8 ano | ||||
| Controle | 177 | 9 ano | ||||
| Experimental | 250 | 6 ano | ||||
| Experimental | 283 | 7 ano | ||||
| Experimental | 258 | 8 ano | ||||
| Experimental | 245 | 9 ano | ||||
| Controle | 112 | 11 | ||||
| Controle | 162 | 12 | ||||
| Controle | 183 | 13 | ||||
| Controle | 172 | 14 | ||||
| Controle | 90 | 15 | ||||
| Controle | 30 | 16 | ||||
| Controle | 9 | 17 | ||||
| Controle | 5 | 18 | ||||
| Controle | 1 | 19 | ||||
| Controle | 2 | 20 | ||||
| Controle | 1 | 21 | ||||
| Controle | 1 | 22 | ||||
| Controle | 1 | 34 | ||||
| Experimental | 1 | 1 | ||||
| Experimental | 160 | 11 | ||||
| Experimental | 215 | 12 | ||||
| Experimental | 226 | 13 | ||||
| Experimental | 220 | 14 | ||||
| Experimental | 126 | 15 | ||||
| Experimental | 52 | 16 | ||||
| Experimental | 21 | 17 | ||||
| Experimental | 7 | 18 | ||||
| Experimental | 3 | 19 | ||||
| Experimental | 1 | 20 | ||||
| Experimental | 1 | 21 | ||||
| Experimental | 1 | 23 | ||||
| Experimental | 1 | 4 | ||||
| Experimental | 1 | 9 |
df <- do.call(rbind, lapply(c("Sexo","Zona","Cor.Raca","Serie","Idade"), FUN = function(x) {
tdat2 <- gdat
tdat2[[x]][is.na(tdat2[[x]])] <- "Not declared"
count_(group_by(tdat2, grupo), x)
}))
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
| grupo | Sexo | n | Zona | Cor.Raca | Serie | Idade |
|---|---|---|---|---|---|---|
| Controle | F | 367 | ||||
| Controle | M | 386 | ||||
| Experimental | F | 502 | ||||
| Experimental | M | 515 | ||||
| Controle | 208 | Not declared | ||||
| Controle | 343 | Rural | ||||
| Controle | 202 | Urbana | ||||
| Experimental | 315 | Not declared | ||||
| Experimental | 421 | Rural | ||||
| Experimental | 281 | Urbana | ||||
| Controle | 76 | Branca | ||||
| Controle | 20 | Indígena | ||||
| Controle | 404 | Not declared | ||||
| Controle | 252 | Parda | ||||
| Controle | 1 | Preta | ||||
| Experimental | 2 | Amarela | ||||
| Experimental | 89 | Branca | ||||
| Experimental | 22 | Indígena | ||||
| Experimental | 610 | Not declared | ||||
| Experimental | 293 | Parda | ||||
| Experimental | 1 | Preta | ||||
| Controle | 213 | 6 ano | ||||
| Controle | 209 | 7 ano | ||||
| Controle | 158 | 8 ano | ||||
| Controle | 173 | 9 ano | ||||
| Experimental | 245 | 6 ano | ||||
| Experimental | 277 | 7 ano | ||||
| Experimental | 253 | 8 ano | ||||
| Experimental | 242 | 9 ano | ||||
| Controle | 112 | 11 | ||||
| Controle | 161 | 12 | ||||
| Controle | 181 | 13 | ||||
| Controle | 166 | 14 | ||||
| Controle | 87 | 15 | ||||
| Controle | 30 | 16 | ||||
| Controle | 7 | 17 | ||||
| Controle | 5 | 18 | ||||
| Controle | 1 | 20 | ||||
| Controle | 1 | 21 | ||||
| Controle | 1 | 22 | ||||
| Controle | 1 | 34 | ||||
| Experimental | 1 | 1 | ||||
| Experimental | 157 | 11 | ||||
| Experimental | 214 | 12 | ||||
| Experimental | 220 | 13 | ||||
| Experimental | 218 | 14 | ||||
| Experimental | 124 | 15 | ||||
| Experimental | 50 | 16 | ||||
| Experimental | 19 | 17 | ||||
| Experimental | 6 | 18 | ||||
| Experimental | 3 | 19 | ||||
| Experimental | 1 | 20 | ||||
| Experimental | 1 | 21 | ||||
| Experimental | 1 | 23 | ||||
| Experimental | 1 | 4 | ||||
| Experimental | 1 | 9 |
df <- do.call(rbind, lapply(c("Sexo","Zona","Cor.Raca","Serie","Idade"), FUN = function(x) {
tdat2 <- gdat[gdat$id %in% dat$id,]
tdat2[[x]][is.na(tdat2[[x]])] <- "Not declared"
count_(group_by(tdat2, grupo), x)
}))
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
| grupo | Sexo | n | Zona | Cor.Raca | Serie | Idade |
|---|---|---|---|---|---|---|
| Controle | F | 247 | ||||
| Controle | M | 238 | ||||
| Experimental | F | 319 | ||||
| Experimental | M | 317 | ||||
| Controle | 133 | Not declared | ||||
| Controle | 243 | Rural | ||||
| Controle | 109 | Urbana | ||||
| Experimental | 185 | Not declared | ||||
| Experimental | 284 | Rural | ||||
| Experimental | 167 | Urbana | ||||
| Controle | 50 | Branca | ||||
| Controle | 11 | Indígena | ||||
| Controle | 262 | Not declared | ||||
| Controle | 162 | Parda | ||||
| Experimental | 1 | Amarela | ||||
| Experimental | 61 | Branca | ||||
| Experimental | 15 | Indígena | ||||
| Experimental | 369 | Not declared | ||||
| Experimental | 190 | Parda | ||||
| Controle | 134 | 6 ano | ||||
| Controle | 141 | 7 ano | ||||
| Controle | 89 | 8 ano | ||||
| Controle | 121 | 9 ano | ||||
| Experimental | 159 | 6 ano | ||||
| Experimental | 187 | 7 ano | ||||
| Experimental | 143 | 8 ano | ||||
| Experimental | 147 | 9 ano | ||||
| Controle | 85 | 11 | ||||
| Controle | 109 | 12 | ||||
| Controle | 115 | 13 | ||||
| Controle | 108 | 14 | ||||
| Controle | 45 | 15 | ||||
| Controle | 14 | 16 | ||||
| Controle | 5 | 17 | ||||
| Controle | 1 | 18 | ||||
| Controle | 1 | 21 | ||||
| Controle | 1 | 22 | ||||
| Controle | 1 | 34 | ||||
| Experimental | 1 | 1 | ||||
| Experimental | 112 | 11 | ||||
| Experimental | 153 | 12 | ||||
| Experimental | 139 | 13 | ||||
| Experimental | 132 | 14 | ||||
| Experimental | 68 | 15 | ||||
| Experimental | 21 | 16 | ||||
| Experimental | 6 | 17 | ||||
| Experimental | 1 | 18 | ||||
| Experimental | 1 | 19 | ||||
| Experimental | 1 | 21 | ||||
| Experimental | 1 | 9 |
df <- do.call(rbind, lapply(names(ldat), FUN = function(tname) {
dat2 <- ldat[[tname]]
data.frame(
"For Analysis of ANCOVA" = tname,
do.call(rbind, lapply(c("Sexo","Zona","Cor.Raca","Serie","Idade"), FUN = function(x) {
tdat2 <- gdat[gdat$id %in% dat2$id,]
tdat2[[x]][is.na(tdat2[[x]])] <- "Not declared"
count_(group_by(tdat2, grupo), x)
})))
}))
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: `count_()` was deprecated in dplyr 0.7.0.
## ℹ Please use `count()` instead.
## ℹ See vignette('programming') for more help
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
| For.Analysis.of.ANCOVA | grupo | Sexo | n | Zona | Cor.Raca | Serie | Idade |
|---|---|---|---|---|---|---|---|
| grupo | Controle | F | 207 | ||||
| grupo | Controle | M | 217 | ||||
| grupo | Experimental | F | 279 | ||||
| grupo | Experimental | M | 278 | ||||
| grupo | Controle | 122 | Not declared | ||||
| grupo | Controle | 220 | Rural | ||||
| grupo | Controle | 82 | Urbana | ||||
| grupo | Experimental | 168 | Not declared | ||||
| grupo | Experimental | 250 | Rural | ||||
| grupo | Experimental | 139 | Urbana | ||||
| grupo | Controle | 40 | Branca | ||||
| grupo | Controle | 11 | Indígena | ||||
| grupo | Controle | 239 | Not declared | ||||
| grupo | Controle | 134 | Parda | ||||
| grupo | Experimental | 1 | Amarela | ||||
| grupo | Experimental | 53 | Branca | ||||
| grupo | Experimental | 14 | Indígena | ||||
| grupo | Experimental | 332 | Not declared | ||||
| grupo | Experimental | 157 | Parda | ||||
| grupo | Controle | 119 | 6 ano | ||||
| grupo | Controle | 106 | 7 ano | ||||
| grupo | Controle | 82 | 8 ano | ||||
| grupo | Controle | 117 | 9 ano | ||||
| grupo | Experimental | 126 | 6 ano | ||||
| grupo | Experimental | 158 | 7 ano | ||||
| grupo | Experimental | 137 | 8 ano | ||||
| grupo | Experimental | 136 | 9 ano | ||||
| grupo | Controle | 78 | 11 | ||||
| grupo | Controle | 79 | 12 | ||||
| grupo | Controle | 100 | 13 | ||||
| grupo | Controle | 104 | 14 | ||||
| grupo | Controle | 42 | 15 | ||||
| grupo | Controle | 12 | 16 | ||||
| grupo | Controle | 5 | 17 | ||||
| grupo | Controle | 1 | 18 | ||||
| grupo | Controle | 1 | 21 | ||||
| grupo | Controle | 1 | 22 | ||||
| grupo | Controle | 1 | 34 | ||||
| grupo | Experimental | 1 | 1 | ||||
| grupo | Experimental | 83 | 11 | ||||
| grupo | Experimental | 138 | 12 | ||||
| grupo | Experimental | 126 | 13 | ||||
| grupo | Experimental | 119 | 14 | ||||
| grupo | Experimental | 63 | 15 | ||||
| grupo | Experimental | 19 | 16 | ||||
| grupo | Experimental | 5 | 17 | ||||
| grupo | Experimental | 1 | 18 | ||||
| grupo | Experimental | 1 | 19 | ||||
| grupo | Experimental | 1 | 21 | ||||
| grupo:Sexo | Controle | F | 208 | ||||
| grupo:Sexo | Controle | M | 211 | ||||
| grupo:Sexo | Experimental | F | 276 | ||||
| grupo:Sexo | Experimental | M | 279 | ||||
| grupo:Sexo | Controle | 119 | Not declared | ||||
| grupo:Sexo | Controle | 219 | Rural | ||||
| grupo:Sexo | Controle | 81 | Urbana | ||||
| grupo:Sexo | Experimental | 164 | Not declared | ||||
| grupo:Sexo | Experimental | 248 | Rural | ||||
| grupo:Sexo | Experimental | 143 | Urbana | ||||
| grupo:Sexo | Controle | 39 | Branca | ||||
| grupo:Sexo | Controle | 11 | Indígena | ||||
| grupo:Sexo | Controle | 234 | Not declared | ||||
| grupo:Sexo | Controle | 135 | Parda | ||||
| grupo:Sexo | Experimental | 1 | Amarela | ||||
| grupo:Sexo | Experimental | 52 | Branca | ||||
| grupo:Sexo | Experimental | 15 | Indígena | ||||
| grupo:Sexo | Experimental | 329 | Not declared | ||||
| grupo:Sexo | Experimental | 158 | Parda | ||||
| grupo:Sexo | Controle | 117 | 6 ano | ||||
| grupo:Sexo | Controle | 106 | 7 ano | ||||
| grupo:Sexo | Controle | 82 | 8 ano | ||||
| grupo:Sexo | Controle | 114 | 9 ano | ||||
| grupo:Sexo | Experimental | 123 | 6 ano | ||||
| grupo:Sexo | Experimental | 158 | 7 ano | ||||
| grupo:Sexo | Experimental | 137 | 8 ano | ||||
| grupo:Sexo | Experimental | 137 | 9 ano | ||||
| grupo:Sexo | Controle | 77 | 11 | ||||
| grupo:Sexo | Controle | 80 | 12 | ||||
| grupo:Sexo | Controle | 99 | 13 | ||||
| grupo:Sexo | Controle | 102 | 14 | ||||
| grupo:Sexo | Controle | 41 | 15 | ||||
| grupo:Sexo | Controle | 11 | 16 | ||||
| grupo:Sexo | Controle | 5 | 17 | ||||
| grupo:Sexo | Controle | 1 | 18 | ||||
| grupo:Sexo | Controle | 1 | 21 | ||||
| grupo:Sexo | Controle | 1 | 22 | ||||
| grupo:Sexo | Controle | 1 | 34 | ||||
| grupo:Sexo | Experimental | 1 | 1 | ||||
| grupo:Sexo | Experimental | 80 | 11 | ||||
| grupo:Sexo | Experimental | 138 | 12 | ||||
| grupo:Sexo | Experimental | 125 | 13 | ||||
| grupo:Sexo | Experimental | 120 | 14 | ||||
| grupo:Sexo | Experimental | 64 | 15 | ||||
| grupo:Sexo | Experimental | 19 | 16 | ||||
| grupo:Sexo | Experimental | 5 | 17 | ||||
| grupo:Sexo | Experimental | 1 | 18 | ||||
| grupo:Sexo | Experimental | 1 | 19 | ||||
| grupo:Sexo | Experimental | 1 | 21 | ||||
| grupo:Zona | Controle | F | 164 | ||||
| grupo:Zona | Controle | M | 165 | ||||
| grupo:Zona | Experimental | F | 201 | ||||
| grupo:Zona | Experimental | M | 210 | ||||
| grupo:Zona | Controle | 228 | Rural | ||||
| grupo:Zona | Controle | 101 | Urbana | ||||
| grupo:Zona | Experimental | 260 | Rural | ||||
| grupo:Zona | Experimental | 151 | Urbana | ||||
| grupo:Zona | Controle | 37 | Branca | ||||
| grupo:Zona | Controle | 11 | Indígena | ||||
| grupo:Zona | Controle | 167 | Not declared | ||||
| grupo:Zona | Controle | 114 | Parda | ||||
| grupo:Zona | Experimental | 46 | Branca | ||||
| grupo:Zona | Experimental | 15 | Indígena | ||||
| grupo:Zona | Experimental | 205 | Not declared | ||||
| grupo:Zona | Experimental | 145 | Parda | ||||
| grupo:Zona | Controle | 110 | 6 ano | ||||
| grupo:Zona | Controle | 110 | 7 ano | ||||
| grupo:Zona | Controle | 49 | 8 ano | ||||
| grupo:Zona | Controle | 60 | 9 ano | ||||
| grupo:Zona | Experimental | 110 | 6 ano | ||||
| grupo:Zona | Experimental | 145 | 7 ano | ||||
| grupo:Zona | Experimental | 73 | 8 ano | ||||
| grupo:Zona | Experimental | 83 | 9 ano | ||||
| grupo:Zona | Controle | 75 | 11 | ||||
| grupo:Zona | Controle | 85 | 12 | ||||
| grupo:Zona | Controle | 73 | 13 | ||||
| grupo:Zona | Controle | 56 | 14 | ||||
| grupo:Zona | Controle | 25 | 15 | ||||
| grupo:Zona | Controle | 9 | 16 | ||||
| grupo:Zona | Controle | 2 | 17 | ||||
| grupo:Zona | Controle | 1 | 18 | ||||
| grupo:Zona | Controle | 1 | 21 | ||||
| grupo:Zona | Controle | 1 | 22 | ||||
| grupo:Zona | Controle | 1 | 34 | ||||
| grupo:Zona | Experimental | 1 | 1 | ||||
| grupo:Zona | Experimental | 73 | 11 | ||||
| grupo:Zona | Experimental | 132 | 12 | ||||
| grupo:Zona | Experimental | 80 | 13 | ||||
| grupo:Zona | Experimental | 64 | 14 | ||||
| grupo:Zona | Experimental | 43 | 15 | ||||
| grupo:Zona | Experimental | 12 | 16 | ||||
| grupo:Zona | Experimental | 4 | 17 | ||||
| grupo:Zona | Experimental | 1 | 19 | ||||
| grupo:Zona | Experimental | 1 | 21 | ||||
| grupo:Cor.Raca | Controle | F | 107 | ||||
| grupo:Cor.Raca | Controle | M | 99 | ||||
| grupo:Cor.Raca | Experimental | F | 121 | ||||
| grupo:Cor.Raca | Experimental | M | 127 | ||||
| grupo:Cor.Raca | Controle | 48 | Not declared | ||||
| grupo:Cor.Raca | Controle | 127 | Rural | ||||
| grupo:Cor.Raca | Controle | 31 | Urbana | ||||
| grupo:Cor.Raca | Experimental | 34 | Not declared | ||||
| grupo:Cor.Raca | Experimental | 173 | Rural | ||||
| grupo:Cor.Raca | Experimental | 41 | Urbana | ||||
| grupo:Cor.Raca | Controle | 45 | Branca | ||||
| grupo:Cor.Raca | Controle | 11 | Indígena | ||||
| grupo:Cor.Raca | Controle | 150 | Parda | ||||
| grupo:Cor.Raca | Experimental | 58 | Branca | ||||
| grupo:Cor.Raca | Experimental | 15 | Indígena | ||||
| grupo:Cor.Raca | Experimental | 175 | Parda | ||||
| grupo:Cor.Raca | Controle | 56 | 6 ano | ||||
| grupo:Cor.Raca | Controle | 54 | 7 ano | ||||
| grupo:Cor.Raca | Controle | 37 | 8 ano | ||||
| grupo:Cor.Raca | Controle | 59 | 9 ano | ||||
| grupo:Cor.Raca | Experimental | 71 | 6 ano | ||||
| grupo:Cor.Raca | Experimental | 53 | 7 ano | ||||
| grupo:Cor.Raca | Experimental | 69 | 8 ano | ||||
| grupo:Cor.Raca | Experimental | 55 | 9 ano | ||||
| grupo:Cor.Raca | Controle | 41 | 11 | ||||
| grupo:Cor.Raca | Controle | 38 | 12 | ||||
| grupo:Cor.Raca | Controle | 52 | 13 | ||||
| grupo:Cor.Raca | Controle | 50 | 14 | ||||
| grupo:Cor.Raca | Controle | 14 | 15 | ||||
| grupo:Cor.Raca | Controle | 7 | 16 | ||||
| grupo:Cor.Raca | Controle | 3 | 17 | ||||
| grupo:Cor.Raca | Controle | 1 | 21 | ||||
| grupo:Cor.Raca | Experimental | 52 | 11 | ||||
| grupo:Cor.Raca | Experimental | 47 | 12 | ||||
| grupo:Cor.Raca | Experimental | 52 | 13 | ||||
| grupo:Cor.Raca | Experimental | 50 | 14 | ||||
| grupo:Cor.Raca | Experimental | 30 | 15 | ||||
| grupo:Cor.Raca | Experimental | 14 | 16 | ||||
| grupo:Cor.Raca | Experimental | 2 | 17 | ||||
| grupo:Cor.Raca | Experimental | 1 | 21 | ||||
| grupo:Serie | Controle | F | 230 | ||||
| grupo:Serie | Controle | M | 225 | ||||
| grupo:Serie | Experimental | F | 301 | ||||
| grupo:Serie | Experimental | M | 300 | ||||
| grupo:Serie | Controle | 129 | Not declared | ||||
| grupo:Serie | Controle | 227 | Rural | ||||
| grupo:Serie | Controle | 99 | Urbana | ||||
| grupo:Serie | Experimental | 176 | Not declared | ||||
| grupo:Serie | Experimental | 270 | Rural | ||||
| grupo:Serie | Experimental | 155 | Urbana | ||||
| grupo:Serie | Controle | 48 | Branca | ||||
| grupo:Serie | Controle | 11 | Indígena | ||||
| grupo:Serie | Controle | 249 | Not declared | ||||
| grupo:Serie | Controle | 147 | Parda | ||||
| grupo:Serie | Experimental | 1 | Amarela | ||||
| grupo:Serie | Experimental | 57 | Branca | ||||
| grupo:Serie | Experimental | 15 | Indígena | ||||
| grupo:Serie | Experimental | 353 | Not declared | ||||
| grupo:Serie | Experimental | 175 | Parda | ||||
| grupo:Serie | Controle | 126 | 6 ano | ||||
| grupo:Serie | Controle | 127 | 7 ano | ||||
| grupo:Serie | Controle | 86 | 8 ano | ||||
| grupo:Serie | Controle | 116 | 9 ano | ||||
| grupo:Serie | Experimental | 150 | 6 ano | ||||
| grupo:Serie | Experimental | 170 | 7 ano | ||||
| grupo:Serie | Experimental | 141 | 8 ano | ||||
| grupo:Serie | Experimental | 140 | 9 ano | ||||
| grupo:Serie | Controle | 81 | 11 | ||||
| grupo:Serie | Controle | 99 | 12 | ||||
| grupo:Serie | Controle | 106 | 13 | ||||
| grupo:Serie | Controle | 104 | 14 | ||||
| grupo:Serie | Controle | 42 | 15 | ||||
| grupo:Serie | Controle | 14 | 16 | ||||
| grupo:Serie | Controle | 5 | 17 | ||||
| grupo:Serie | Controle | 1 | 18 | ||||
| grupo:Serie | Controle | 1 | 21 | ||||
| grupo:Serie | Controle | 1 | 22 | ||||
| grupo:Serie | Controle | 1 | 34 | ||||
| grupo:Serie | Experimental | 1 | 1 | ||||
| grupo:Serie | Experimental | 104 | 11 | ||||
| grupo:Serie | Experimental | 147 | 12 | ||||
| grupo:Serie | Experimental | 133 | 13 | ||||
| grupo:Serie | Experimental | 122 | 14 | ||||
| grupo:Serie | Experimental | 65 | 15 | ||||
| grupo:Serie | Experimental | 21 | 16 | ||||
| grupo:Serie | Experimental | 5 | 17 | ||||
| grupo:Serie | Experimental | 1 | 18 | ||||
| grupo:Serie | Experimental | 1 | 19 | ||||
| grupo:Serie | Experimental | 1 | 21 | ||||
| grupo:score.tde.quintile | Controle | F | 223 | ||||
| grupo:score.tde.quintile | Controle | M | 223 | ||||
| grupo:score.tde.quintile | Experimental | F | 285 | ||||
| grupo:score.tde.quintile | Experimental | M | 286 | ||||
| grupo:score.tde.quintile | Controle | 126 | Not declared | ||||
| grupo:score.tde.quintile | Controle | 227 | Rural | ||||
| grupo:score.tde.quintile | Controle | 93 | Urbana | ||||
| grupo:score.tde.quintile | Experimental | 171 | Not declared | ||||
| grupo:score.tde.quintile | Experimental | 256 | Rural | ||||
| grupo:score.tde.quintile | Experimental | 144 | Urbana | ||||
| grupo:score.tde.quintile | Controle | 44 | Branca | ||||
| grupo:score.tde.quintile | Controle | 10 | Indígena | ||||
| grupo:score.tde.quintile | Controle | 247 | Not declared | ||||
| grupo:score.tde.quintile | Controle | 145 | Parda | ||||
| grupo:score.tde.quintile | Experimental | 1 | Amarela | ||||
| grupo:score.tde.quintile | Experimental | 56 | Branca | ||||
| grupo:score.tde.quintile | Experimental | 15 | Indígena | ||||
| grupo:score.tde.quintile | Experimental | 336 | Not declared | ||||
| grupo:score.tde.quintile | Experimental | 163 | Parda | ||||
| grupo:score.tde.quintile | Controle | 123 | 6 ano | ||||
| grupo:score.tde.quintile | Controle | 118 | 7 ano | ||||
| grupo:score.tde.quintile | Controle | 87 | 8 ano | ||||
| grupo:score.tde.quintile | Controle | 118 | 9 ano | ||||
| grupo:score.tde.quintile | Experimental | 138 | 6 ano | ||||
| grupo:score.tde.quintile | Experimental | 160 | 7 ano | ||||
| grupo:score.tde.quintile | Experimental | 136 | 8 ano | ||||
| grupo:score.tde.quintile | Experimental | 137 | 9 ano | ||||
| grupo:score.tde.quintile | Controle | 79 | 11 | ||||
| grupo:score.tde.quintile | Controle | 92 | 12 | ||||
| grupo:score.tde.quintile | Controle | 104 | 13 | ||||
| grupo:score.tde.quintile | Controle | 106 | 14 | ||||
| grupo:score.tde.quintile | Controle | 43 | 15 | ||||
| grupo:score.tde.quintile | Controle | 13 | 16 | ||||
| grupo:score.tde.quintile | Controle | 5 | 17 | ||||
| grupo:score.tde.quintile | Controle | 1 | 18 | ||||
| grupo:score.tde.quintile | Controle | 1 | 21 | ||||
| grupo:score.tde.quintile | Controle | 1 | 22 | ||||
| grupo:score.tde.quintile | Controle | 1 | 34 | ||||
| grupo:score.tde.quintile | Experimental | 1 | 1 | ||||
| grupo:score.tde.quintile | Experimental | 92 | 11 | ||||
| grupo:score.tde.quintile | Experimental | 142 | 12 | ||||
| grupo:score.tde.quintile | Experimental | 126 | 13 | ||||
| grupo:score.tde.quintile | Experimental | 118 | 14 | ||||
| grupo:score.tde.quintile | Experimental | 64 | 15 | ||||
| grupo:score.tde.quintile | Experimental | 20 | 16 | ||||
| grupo:score.tde.quintile | Experimental | 5 | 17 | ||||
| grupo:score.tde.quintile | Experimental | 1 | 18 | ||||
| grupo:score.tde.quintile | Experimental | 1 | 19 | ||||
| grupo:score.tde.quintile | Experimental | 1 | 21 |